COMMISSION STAFF WORKING DOCUMENT Equipping Europe for world-class High Performance Computing in the next decade Accompanying the document Proposal for a Council Regulation on Establishing the European High Performance Computing Joint Undertaking
Date: 2020-09-18
Institutions: Directorate-General for Communications Networks, Content and Technology, European Commission
Subjects: EU initiative, EU research policy, European Joint Undertaking, computer system, computer systems, data processing, innovation, new technology, scientific cooperation

EN 

  EN 

   EUROPEAN COMMISSION  Brussels, 18.9.2020  SWD(2020) 179 final  COMMISSION STAFF WORKING DOCUMENT Equipping Europe for world-class High Performance Computing in the next decade       Accompanying the document Proposal for a Council Regulation  on Establishing the European High Performance Computing Joint Undertaking {COM(2020) 569 final}  
 
 
Table of Contents 

Executive Summary ................................................................................................................... 2 

1.  Introduction ........................................................................................................................... 6 

2.  The European strategy on HPC: state of play ........................................................................ 8 
2.1 A brief overview of the Union’s policy in HPC ....................................................... 8 
2.2 The EuroHPC Joint Undertaking and its current mission and activities .................. 8 
2.3 Main achievements of the EuroHPC JU in its first year of operations .................. 12 
2.4 The EuroHPC strategy and its impact on the HPC value chain ............................. 20 
2.5 Lessons learnt from the EuroHPC JU governance and administration .................. 21 

3.  HPC in a fast evolving environment .................................................................................... 23 
3.1 The increasing importance of HPC for a wide range of applications .................... 23 
3.2 HPC Market drivers ............................................................................................... 25 
3.3 Evolution of user requirements .............................................................................. 27 
3.4 The convergence of HPC with AI .......................................................................... 29 
3.5 Evolution of supercomputing technologies ............................................................ 30 
3.6 New computing paradigms Neuromorphic and Quantum Computing ................... 31 
3.7 Training and skills for the next decade .................................................................. 33 
3.8 New political guidelines and Commission priorities for the period 2019-2024 .... 34 

4.  The Union’s HPC strategic approach for the next MFF (2021-2027) ................................. 36 
4.1 Rationale for a new mission of the EuroHPC JU in the next MFF ........................ 36 
4.2 The mission of the EuroHPC JU in the next MFF ................................................. 37 

5.  The main activities of EuroHPC JU in the next MFF ......................................................... 40 
5.1 The new pillars of activity ...................................................................................... 40 
5.2 The supporting programmes of the next MFF ....................................................... 46 
5.3 Interactions and synergies with other strategic objectives and policies ................. 47 
5.4 International Cooperation ....................................................................................... 48 
Acronyms and abbreviations .................................................................................................... 50 

List of Figures .......................................................................................................................... 52 

Annex I: Market Analysis and Investments ............................................................................. 53 
The economic impact of HPC ...................................................................................... 53 
The HPC market ........................................................................................................... 55 
Europe and the HPC Market ........................................................................................ 57 
Uses of HPC with AI and Cloud .................................................................................. 58 
HPC worldwide investments: the strategic race towards exascale computing ............ 60 

Annex II: HPC and AI .............................................................................................................. 64 

Annex III: Applications of HPC ............................................................................................... 71 
The data revolution and the strategic digital autonomy ............................................... 71 
HPC and industry’s innovation potential ..................................................................... 72 
Scientific leadership ..................................................................................................... 74 
Societal challenges, policy making and national security ............................................ 75 
HPC and the COVID-19 crisis ..................................................................................... 78 

Endnotes and web references ................................................................................................... 81 

 
 
Executive Summary 

This  Staff  Working  Document  (SWD)  outlines  the  continuation  of  Europe’s  ambitious 
strategic approach in  High Performance Computing  (HPC) for  the next  decade. HPC  is  an 
essential digital infrastructure for achieving the Commission’s aim of maximising the benefits 
of digitisation for everyone as outlined in the Commission Communications on “A European 
strategy for data”1 and “Shaping Europe’s Digital Future”2, and one of the priority recovery 
investments identified in “Europe's moment: Repair and Prepare for the Next Generation”. 3 

The SWD accompanies the Commission proposal for a revised Regulation on the EuroHPC 
Joint  Undertaking  (EuroHPC  JU).  It  provides  an  updated  information  to  the  JU’s  Impact 
Assessment that was held in 2018,4 and that is still applying to a large extent as the JU was 
only established late 2018. The SWD builds on the European strategy on HPC implemented in 
the  period  2012-2020  and  analyses  the  evolution  of  this  strategy  since  the  launch  of  the 
EuroHPC JU, which has become the strategy’s main implementation body. 

HPC is a critical capability for the digital transformation of our society, and is the “engine” 
that powers the data economy, enabling key technologies like Artificial Intelligence (AI), data 
analytics and cybersecurity to exploit the enormous potential of big data.  

HPC is used in more than 800 scientific, industrial and public sector applications that play a 
major  role  in  boosting  industry’s  innovation  capability,  advancing  science,  and  improving 
citizens’ quality of life. Europe is today a leader in HPC applications in a wide range of areas 
such  as  personalised  medicine,  weather  forecasting,  the  design  of  new  aeroplanes,  cars, 
materials, and drugs, and energy, engineering and manufacturing.  

HPC enables many industrial sectors to innovate and to move up into higher value products 
and  services  paving  the  way  to  novel  industrial  applications  in  combination  with  other 
advanced  digital  technologies.  HPC  applications  and  infrastructures  are  essential  in  nearly 
every  field  of  research  for  deeper  scientific  understanding  and  breakthroughs  from 
fundamental physics to biomedicine. HPC is also an essential tool for researchers and policy-
makers  to  address  major  societal  challenges,  from  climate  change,  smart  and  green 
development, and sustainable agriculture to personalised medicine and crisis management. A 
good example is the COVID-19 pandemic, where HPC is used, often in combination with AI, 
to accelerate the discovery of new drugs, predict the virus’ spread, plan and distribute scarce 
medical  resources,  and  anticipate  the  effectiveness  of  different  containment  measures  and 
post-epidemic scenarios. Another good example is the EU Destination Earth initiative5 which 
aims to use vast amounts of data gathered from satellite and terrestrial data and build a high-
precision  digital  model  of  the  Earth  to  monitor  and  simulate,  by  using  HPC,  natural  and 
human activity. Destination Earth would provide to a large number of users applications and 
services such as weather forecasting, urban and rural planning, waste and water management 
and oceanographic, marine and frozen environment modelling. This will help speed up the EU 
green  transition  objectives  and  assist  in  preparing  for  as  well  as  managing  major 
environmental degradation and disasters. 

Europe’s  leading  role  in  the  data  economy,  its  scientific  excellence,  and  its  industrial 
competitiveness will increasingly depend on its capability to autonomously develop key HPC 
technologies,  reducing  dependence  on  foreign  providers,  provide  access  to  world-class 
supercomputing and data infrastructures, and maintain global leadership in HPC applications. 
To make this happen, a pan-European strategic approach is essential. 

2 

 
 
The EuroHPC JU was  established in  2018 as  a Joint Undertaking under  Article 187 TFEU, 
pooling resources from the EU, 32 countries (EU Member States and countries associated to 
Horizon  2020),  and  two  Private  Members:  the  European  Technology  Platform  for  HPC 
(ETP4HPC) and the Big Data Value (BDVA) Associations. 

After  two  years  of  operation,  the  EuroHPC  JU  has  substantially  increased  the  overall 
investment  in  HPC  at  European  level  and  has  started  to  deliver  on  its  mission  to  restore 
Europe’s position as a leading HPC power globally. By the end of 2020, it will deploy a first-
class  supercomputing  and  data  infrastructure  accessible  to  public  and  private  users  all  over 
Europe. Investments under the current Regulation will also support HPC Competence Centres 
throughout  Europe,  the  development  of  HPC  skills,  and  R&I  in  critical  HPC  hardware  and 
software  technologies  and  applications,  increasing  the  EU’s  capability  to  autonomously 
produce and use competitive HPC technology.  

For the strategic investments made so far, the EuroHPC JU has used funds from the current 
Multiannual Financial Framework (MFF). The implementation of the European HPC strategy 
with funds from the next MFF requires a revision of the EuroHPC Council Regulation.6  

This  SWD  describes  the  essential  role  HPC  will  play  in  the  next  MFF  period  for  the  EU’s 
competitiveness,  the  digital  transformation  of  Europe,  and  the  creation  of  European  public 
common data spaces. It provides evidence of the importance of the EuroHPC JU’s activities, 
and  of  the  impact  that  its  continuation  will  have  on  an  increasing  number  of  critical 
technologies  and  applications  in  the  next  decade,  notably  for  European  leadership  in  low-
power processor technologies and in AI.7 The SWD also analyses the key socio-economic and 
technological  drivers  affecting  the  future  evolution  of  HPC  and  data  infrastructures, 
technologies and applications in the EU and worldwide, including the EU’s political priorities 
for 2020-2025.  

One of the most important technological drivers that the SWD considers is the emergence of 
quantum  computing.  Initial  quantum  computing  systems  already  exist  mostly  in  an 
experimental form; larger systems are expected to become available in the period 2021-2027 
that could operate next to or be integrated with traditional HPC systems.  

The  revision  of  the  Council  Regulation  provides  an  opportunity  to  update  the  mission  and 
objectives  of  the  EuroHPC  JU,  taking  into  consideration  these  new  drivers  and  the  lessons 
learnt from the JU’s current activities. This SWD suggests an updated mission for the JU:  

By 2027, develop, deploy, extend and maintain in the Union a world leading federated, secure  
and  hyper-connected  supercomputing,  quantum  computing  service  and  data  infrastructure 
ecosystem;  support  the  production  of  innovative  and  competitive  supercomputing  systems 
based  on  a  supply  chain  that  will  ensure  components,  technologies  and  knowledge  limiting 
the  risk  of  disruptions  and  the  development  of  a  wide  range  of  applications  optimised  for 
these  systems;  widen  the  use  of  this  supercomputing  infrastructure  to  a  large  number  of 
public and private users, and support the development of key skills for European science and 
industry. 

The roadmap for the development and deployment of the federated computing infrastructure 
of the EuroHPC JU is summarised in the table below (including infrastructure investments for 
2019-2020).  Investments  in  the  period  2021-2027  will  target  an  ambitious  combination  of 
interconnected world-class HPC and quantum computing systems:  

3 

 
 
 
2019 

2020 

2021  2022 

2023 

2024 

2025 

2026  2027 

HPC 
Infrastructure 

3 pre-exascale and 
5 petascale HPC 
systems 

Several pre-exascale systems 
and 2 exascale HPC systems 

Quantum  
Infrastructure 

Quantum 
simulators 
interfacing 
with HPC 
systems 

First 
generation 
of quantum 
computers  

Quantum 
simulators 
interfacing 
with HPC 
systems 

One or more exascale 
and post-exascale 
HPC systems 

Second generation of 
quantum computers  

In  order  to  realise  this  mission  and  roadmap,  the  SWD  identifies  the  following  overall 
objectives for the continuation of the EuroHPC JU:  

1.  Deploy  and  maintain  in  the  Union  a  secure,  hyper-connected  and  integrated  world-class 
HPC, quantum computing and data infrastructure, based on the best existing computing, 
data and networking technologies; 

2.  Federate the HPC, quantum computing service and data infrastructure, interconnect it with 
the European public data spaces and cloud ecosystem, and provide EU-wide services to a 
wide range of public and private users; 

3.  Develop and support an innovative HPC and data ecosystem contributing to the standing 
and  technological  autonomy  of  the  Union  in  the  digital  economy,  capable  to  produce 
leading 
into 
computing 
supercomputing systems, and advanced applications optimised for these systems;  

technologies  and  architectures  and 

integration 

their 

4.  Widen the use of HPC and develop the key skills that European science and industry need. 

The main expected outcomes for the EuroHPC JU in the next decade would include: 

  A federated, secure and hyper-connected European HPC and data infrastructure with mid-
range supercomputers and at least two top class exascale and two top class post-exascale 
systems (integrating as much as possible European technology); 

  Hybrid  computing  infrastructures  integrating  advanced  computing  systems  –  notably 

quantum simulators and quantum computers – in HPC infrastructures; 

  A secure cloud-based HPC and data infrastructure for European private users; 
  HPC-powered capacities and services based on European public data spaces for scientists, 

industry and the public sector; 

  Next generation technology building blocks (hardware and software) and their integration 

into innovative HPC architectures for exascale and post-exascale systems; 

  Centres  of  Excellence  in  HPC  applications  and  industrialisation  of  HPC  software,  with 
novel algorithms, codes and tools optimised for future generations of supercomputers; 
  Large-scale  industrial  pilot  test-beds  and  platforms  for  HPC  and  data  applications  and 

services in key industrial sectors; 

  National  HPC  Competence  Centres,  ensuring  a  wide  coverage  of  HPC  in  the  EU,  with 

specific services and resources for industrial innovation (including SMEs); 
  A significant increase for Europe’s workforce in HPC skills and know-how; 
  Reinforced  data  storage,  processing  capacities,  and  new  services,  in  areas  of  public 

interest across the Member States. 

4 

 
 
 
 
 
 
To  achieve  these  objectives,  the  SWD  advocates  an  all-encompassing  approach  covering 
national  and  EU  investments,  the  participation  of  industrial  Private  Members,  and  close 
collaboration  with  key  European  actors  such  as  PRACE8  and  GEANT.9  The  EuroHPC  JU 
should also foster international collaboration that benefits the EU. 

Finally, the SWD advocates for the EuroHPC JU to operate in synergy with actions in major 
EU priority areas, namely AI, cybersecurity, quantum technologies, big data, European public 
common  data  spaces,,  and  advanced  digital  skills.  This  would  require  collaboration  with 
initiatives  such  as  the  Joint  Undertaking  on  Key  Digital  Technologies,  the  Quantum 
Technologies  Flagship,10  and  the  European  partnerships  on  AI,  data,  cybersecurity  and  the 
European Open Science Cloud. The EuroHPC JU should also forge links and synergies with 
other EU and national programmes and their stakeholders. 

5 

 
 
1.  Introduction 

This  Staff  Working  Document  (SWD)  accompanies  a  Commission  proposal  for  the  revised 
Regulation  for  the  EuroHPC  Joint  Undertaking,  covering  the  period  2021-2033.i  The  SWD 
analyses  the  evolution  of  the  main  factors  affecting  the  European  strategy  in  High 
Performance Computing (HPC), in particular since the establishment in 2018 of the EuroHPC 
Joint Undertaking (EuroHPC JU).5  

The reasons behind the creation of the EuroHPC JU are presented in the corresponding 2018 
Impact  Assessment4,  which  is  still  applicable  for  the  continuation  of  the  JU.  This  SWD 
provides an update on the supporting data of that Impact Assessment and provides evidence to 
support the continuation of the EuroHPC JU as a main instrument to implement the European 
HPC  strategy.  It  describes  the  key  role  that  HPC  will  continue  to  play  in  the  Union’s 
competitiveness and the digital transformation of the European economy and society. It sets 
out  the  increasing  number  of  industrial,  scientific  and  public  sector  applications  and  user 
needs that will benefit from continuing the EuroHPC JU.  

The SWD is structured as follows: 

  Chapter 1 provides a brief overview of the EU policy on HPC; 

  Chapter  2  presents  the  role  and  achievements  of  the  EuroHPC  JU  for  the  European 

strategy on HPC and the lessons learnt since its establishment in 2018; 

  Chapter 3 analyses the main drivers that are likely to affect the evolution of HPC in the 
next  decade.  They  include  the  increasing  importance  of  HPC  for  a  wide  range  of 
applications,  the  evolution  of  the  market,  user  requirements,  developments  in  the 
underlying  technology,  notably  in  quantum  computing,  and  the  new  political  factors  to 
consider; 

  Chapter 4 describes the suggested mission and mandate of the EuroHPC JU in the period 

2021-2027, taking into consideration the drivers analysed in Chapter 3; 

  Chapter  5  presents  the  suggested  main  implementation  activities  of  the  EuroHPC  JU  in 

the period 2021-2027 and the different instruments to support such implementation; 

  The Annexes gather the supporting data, in particular on the economic impact of HPC, the 
evolution of the world market and investments, and the key convergence of HPC with AI. 
They  also  provide  representative  examples  of  the  key  HPC  applications  in  different 
domains,  and  illustrate  the  important  role  of  HPC  in  tackling  global  crises,  such  as  the 
COVID-19. 

What is High Performance Computing (HPC) and why is it important? 

The term “High Performance Computing” is used in this document as a synonym for high-end 
computing, supercomputing or world-class computing, dealing with problems so demanding, 
that the massive computations needed to solve them cannot be performed by general-purpose 

i   This  covers  the  next  MFF  (2021-2027),  the  period  required  for  depreciating  the  operation  of  any 
supercomputer(s) that the JU  may acquire at the  very end  of the  MFF  - typically 5  years  -, and the period 
required for winding up the JU. 

6 

 
 
                                                 
computers.  Instead, 
supercomputers. 

they  require  very  powerful  systems,  called  HPC  systems  or 

A supercomputer interconnects a large number of processors (from a few hundred to several 
thousand) working in parallel. The fastest supercomputersii are currently achieving petascale 
performance,  and  the  next  frontier  is  the  exascale  computing.  Supercomputing  power  is 
currently  increasing  so  fast  that  world-class  machines  are  becoming  obsolete  after,  on 
average, 5-6 years. As an example, an ordinary laptop today has the computing power of the 
world's top supercomputer 25 years ago.  

HPC methodologies include modelling and simulation, and are frequently associated with big 
data analytics, visualisation, AI (e.g. machine and deep learning), and other techniques. HPC 
powers hundreds of applications across virtually all branches of science, industry and sectors, 
including  the  public  sector.  Representative  examples  of  such  applications  include: 
personalised  medicine,  models  for  climate  change,  earth  observation,  precision  agriculture, 
engineering  and  manufacturing,  cybersecurity,  and  oil  and  gas  exploration.  This  SWD  does 
not  aim to provide an exhaustive list  of all HPC applications. However numerous examples 
are  presented  in  the  Annexes.  Examples  of  the  application  areas  currently  supported  in 
projects funded under Horizon 202011 and the Connecting Europe Facility12 (CEF) include: 

  Horizon 2020 support for HPC Centres of Excellence in areas such as weather and climate 
prediction, materials, energy, biomolecular and biomedical sciences. Large scale industrial 
pilots are supported in the areas of digital twins, health, precision agriculture and farming, 
finance and insurance. A specific project (Esxcalate4CoV, see box below) has been set up 
to develop solutions for COVID-19.  

  Projects funded by under CEF-Telecom address HPC supporting application areas such as 
smart  agriculture,  forestry  evolution  and  fire  control,  air  quality  and  pollution, 
atmospheric, marine and earth observation, and cultural heritage in the EU.  

 

In  2019  the  EuroHPC  JU  launched  a  Call  for  HPC  powered  innovative  applications  in 
sectors of societal and industrial  relevance for Europe. Selected projects  are expected to 
start in autumn 2020. 

HPC and the COVID-19 pandemic 

The  global  COVID-19  crisis  illustrates  how  HPC  in  combination  with  other  digital 
technologies  such  as  big  data  and  AI  can  be  critical  in  the  fight  against  the  pandemic  by 
supporting  the  decision-making  on  containment  measures  and  dramatically  accelerating  the 
development of a treatment or a vaccine.  

smArt 

pLatform  Against 

An  outstanding  example  of  the  European  effort  is  the  EU  funded  “Esxcalate4CoV”  project 
(EXaSCale 
see 
https://www.exscalate4cov.eu/),  which  uses  massive  supercomputing  resources  (more  than 
120 Petaflops) from 4 European HPC systems to analyse the effectiveness of over 500 billion 
pharmacological  molecules  against  the  COVID-19  viral  proteins  that  are  key  for  its 
propagation.  Using  classical  computing  methods,  the  analysis  of  each  molecule  would  take 

–  Corona  Virus 

paThogEns 

– 

ii  The  most  powerful  supercomputer  as  of  June  2020  is  Fugaku  (Japan),  with  514  petaflops  of  peak 
performance (https://www.top-500.org/). A flop is one floating point operations per second. One petaflop is 
1015 (ten to the power of 15 or one million billion) flops. One exaflop is 1018 (ten to the power of 18 or 1 
billion billion) flops. 

7 

 
 
                                                 
several  months,  while  the  HPC  simulation  can  do  so  in  just  50  milliseconds.  Over  100 
molecules  have  been  selected  so  far  for  biological  screening  and  clinical  testing  that  could 
lead to eventual identification and production of a treatment.  

The use of HPC resources with big data sets, deep learning methods and large-scale complex 
computational  models  is  also  critical  to  effectively  support  policymakers  during  epidemic 
emergencies. It helps to rapidly forecast the trajectory of the spread of an infectious disease, 
planning  the  public  health  policy  response,  as  well  as  simulating  the  efficiency  of  different 
containment measures and evaluating the different post-epidemic scenarios. 

2.  The European strategy on HPC: state of play  

2.1 A brief overview of the Union’s policy in HPC 

In  the  last  few  years,  the  ambition  of  the  Union  has  been  to  be  among  the  world's  top 
supercomputing powers and provide everywhere in the Union an integrated world-class HPC 
capability, high-speed connectivity and leading-edge data and software services.  

The  EuroHPC  JU  was  established  to  implement  the  Union’s  strategy  on  HPC  developed  in 
several  Commission  Communications  since  2012:  COM(2012)  45  final13,  COM(2016)  178 
final14, COM(2017) 228 final15, and further supported by the Competitiveness Council (May 
201316  and  May  201617),  the  European  Council  (June  201618),  the  European  Parliament 
(January 201719), and the Telecommunications Council (June 202020). 

In the decade 2008-2018, more than EUR 1.2 billion of the EU budget was invested in HPC 
activities through several programmes: 

 

 

In  2008-2013,  around  EUR  145  million,  from  the  7th  EU  Framework  Programme  for 
Research and Innovation (FP7)21; 
In  2014-2020,  around  EUR  1135  million,  from  Horizon  202011  and  the  Connecting 
Europe Facility12 (CEF, in particular under CEF-Telecom). 

From 2014 onwards, a contractual public-private-partnership (cPPP) between the Commission 
and the European Technology Platform (ETP4HPC) Association22 was established. This cPPP 
lasted until the set-up of the EuroHPC JU in 2018. 

For  the  next  MFF,  the  EuroHPC  JU  would  work  in  synergy  with  other  major  EU  priority 
areas identified in several Commission Communications, in particular  “A European strategy 
for  data”1,  ”Shaping  Europe’s  Digital  Future”2  and  the  “White  Paper  on  Artificial 
Intelligence”7.  HPC  has  also  been  identified  in  the  Communication  “Europe's  moment: 
Repair  and  Prepare  for  the  Next  Generation”3  as  a  strategic  digital  capacity  that  will  be  a 
priority  of  European  recovery  investments  such  as  the  Recovery  and  Resilience  Facility, 
InvestEU and the Strategic Investment Facility. 

2.2 The EuroHPC Joint Undertaking and its current mission and activities 

The EuroHPC JU was established on 28 September 2018 by a Council Regulation6. Its current 
Members  are  the  Union  (represented  by  the  Commission),  32  Participating  Statesiii  (26 

iii   26 Member States (Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, 
France,  Germany,  Greece,  Hungary,  Ireland,  Italy,  Latvia,  Lithuania,  Luxembourg,  Netherlands,  Poland, 

8 

 
 
                                                 
Member States and 6 Countries associated to Horizon 2020), and two Private Members: the 
European Technology Platform for High Performance Computing Association (ETP4HPC)22 
and  the  Big  Data  Value23  Association  (BDVA).  EuroHPC  also  relies  on  collaboration  with 
key European actors such as PRACE (Partnership  for Advanced Computing in  Europe) and 
GEANT (the pan-European high-speed network for research and education).  

Figure 1 - Map of the EuroHPC JU Participating Countries 

The mission of the EuroHPC JU as stated in  the current  Regulation of 2018 is  “to  develop, 
deploy, extend and maintain in the Union an integrated world-class supercomputing and data 
infrastructure  and  to  develop  and  support  a  highly  competitive  and  innovative  High-
Performance  Computing  ecosystem”,  for  the  next-generation  exascale  supercomputing  era 
and beyond.  

The EuroHPC JU has become the strategic instrument for supporting EU competitiveness in 
the global digital economy. The JU mobilises critical national and Union efforts around a joint 
strategy  to  provide  Europe  with  world-class  supercomputing  capabilities  and  knowledge 
according  to  its  economic  potential,  aiming  at  technological  autonomy  in  critical  HPC 
technologies and infrastructures. 

The  Union’s  digital  autonomy  in  HPC  requires  the  capacity  of  developing  world  class 
infrastructures  integrating  as  much  as  possible  top-quality  European  technology.  The 
objectives of the current EuroHPC JU reflect the need to invest in both the deployment of a 
world-class infrastructure and the development of a full European HPC ecosystem.iv 

Portugal,  Romania,  Slovakia,  Slovenia,  Spain  and  Sweden)  plus  6  Associated  Countries  (Iceland, 
Montenegro, North Macedonia, Norway, Switzerland and Turkey).  

iv   According to the Regulation 2018/1488, the main objectives of the JU are:  

9 

 
 
 
                                                                                                                                                         
Establishment, budget and activities under the current Regulation 

The  EuroHPC  JU  was  initially  established  for  the  period  2019  to  2026.  The  initial  co-
investment  of  the  Union  and  the  Participating  States  is  around  EUR  1.1  billion,  with  the 
Union contributing EUR 536 million from the current MFF (2014-2020), and the remainder 
coming from the Participating States. The Private Members will contribute an additional EUR 
422 million in the form of in-kind contributions. The governance structure of the EuroHPC JU 
is  described  in  the  Council  Regulation.  Currently,  the  Commission  ensures  the  transitional 
period until the full autonomy of the JU (expected in Q4 2020). In accordance with its work 
for 2019 and 2020, the EuroHPC JU is supporting the following two main types of activities: 
1.  Acquisition of HPC infrastructure: Eight sites were recently selected24 to host top world-
class supercomputers. They are located in Member States and are supported also by many 
Participating States of the JU, giving a very wide geographical coverage to the initiative: 
  Three precursors-to-exascalev supercomputers aiming to be classed in the world top 5 
supercomputers. The hosting entities and supporting consortia are the following: 

BSC (Barcelona), Spain, with Croatia, Portugal and Turkey 

CINECA (Bologna), Italy, with Austria, Slovenia, Slovakia and Hungary 

CSC (Kajaani), Finland, with Belgium, Czech Republic, Denmark, Estonia, Norway, 
Poland, Sweden, and Switzerland 

The EuroHPC JU will own these systems and will support 50% of their total cost of 
ownership  (TCO).  The  JU  will  have  50%  of  the  total  computing  access  rights.  The 
other  50%  will  be  with  the  Member  State  of  the  hosting  site  and  its  supporting 
consortia. 

  Five petascalevi supercomputers, aiming at ranking in the global top-50 systems. The 

hosting entities and the supporting consortia of partners are the following 

FCT, Portugal, with Spain 

(a)  To provide the research and scientific community, as well as the industry, including SMEs, and the public 
sector from the Union or countries associated to Horizon 2020 with the best available and competitive HPC 
and  data  infrastructure  and  to  support  the  development  of  its  technologies  and  its  applications  across  a 
wide range of fields;  
(b) To  provide  a  framework  for  the  acquisition  of  an  integrated,  demand-oriented  and  user-driven  world-

class supercomputing and data infrastructure in the Union;  

(c) To  provide  Union-level  coordination  and  adequate  financial  resources  to  support  the  development  and 
acquisition  of  such  infrastructure,  which  will  be  accessible  to  users  from  the  public  and  private  sector 
primarily for research and innovation purposes;  

(d) To support an ambitious research and innovation agenda to develop and maintain in the Union a world-
class HPC ecosystem, exascale and beyond, covering all scientific and industrial value chain segments, 
including low-power processor and middleware  technologies, algorithms and code design, applications 
and  systems,  services  and  engineering,  interconnections,  knowledge  and  skills,  for  the  next  generation 
supercomputing era;  

(e) To promote the uptake and systematic use of research and innovation results generated in the Union by 

users from science, industry, including SMEs, and the public sector. 

v   Capable of executing more than 150 Petaflops, or 150 million billion calculations per second 
vi   Capable of executing at least 4 Petaflops 

10 

 
 
                                                                                                                                                         
IT4Innovations, Czech Republic 

LuxProvide S.A., Luxembourg  

Sofia Tech Park, Bulgaria 

IZUM, Slovenia 

The  EuroHPC  JU  and  the  Member  State  of  the  hosting  site  will  jointly  own  these 
systems.  The EuroHPC  JU will support 35% of the acquisition costs of the systems, 
and  will  have  35%  of  the  total  computing  access  rights.  The  Member  State  of  the 
hosting site (with their associated Participating States) will support the rest of the TCO 
and will have 65% of computing access rights for their own use. 

The EuroHPC JU signed specific hosting agreements with each of the 8 hosting sites that 
define the acquisition and operation procedures and the funding arrangements for the new 
supercomputers.  The  acquisition  process  started  in  the  last  quarter  of  2019.  The 
supercomputers  are  expected  to  be  installed  during  the  second  half  of  2020  and  will  be 
interconnected  and  connected  to  the  existing  national  supercomputers  of  the  PRACE 
members through the GEANT network. 

2.  Funding  strategic  Research  and  Innovation  (R&I)  actions  through  calls  for  proposals 
contributing  to  the  EuroHPC  JU’s  mission  to  develop  and  support  a  highly  competitive 
and innovative HPC ecosystem.  
  For 2019, EuroHPC has launched a Call for R&I actions25 for EUR 190 million that 
supports  the  development  of  essential  technologies  for  exascale  systems,  industry-
oriented  HPC  application  platforms,  and  industrial  software  codes;  innovation 
activities  for  manufacturing  and  engineering  SMEs;  and  the  establishment  of  HPC 
competence centres in the Participating States and the coordination of their activities 
at European level. 

  For 2020, the plan is to invest  another EUR 170 million  in supporting the following 
R&I  activities:  funding  the  next  phase  of  the  European  Processor  Initiative  (EPI)26 
(see box below); the integration of European technologies in advanced pilots that will 
lay  the  basis  for  developing  future  European  exascale  supercomputers;  training  and 
education in HPC; and pilots on quantum simulators. 

 

In  addition  to  the  above,  two  Horizon  2020  Calls  for  proposals  will  be  launched  in 
2020, one for complementing the current 9 HPC Centres of Excellence27 for scientific 
leadership  in  HPC  applications,  and  one  on  promoting  International  Cooperation28, 
with the aim of developing a strategic partnership in HPC with Latin America. 

The  European  Processor  Initiative  (EPI)  is  a  5-year  ambitious  large-scale  European 
initiative  aiming  to  develop  critical  low-power  microprocessor  technology.  The  EPI 
consortium brings together 23 partners from 10 European countries. The first phase started in 
December 2018 under Horizon 2020 with EUR 80 million of EU funding. The EuroHPC JU 
plans to support the second phase of EPI, as of 2020. 

EPI  will  develop  components  developed  to  cover  not  only  the  HPC  sector  but  also  broader 
markets and domains (e.g. extreme-scale, big-data and emerging applications based on edge 
computing) that demand high-end computing capabilities such as autonomous driving. A new 
European semiconductor company (Si-pearl) is tasked to commercialise the results of EPI.  

11 

 
 
The  EuroHPC  JU  plans  to  launch  a  call  in  2020  aiming  to  integrate  the  EPI-based 
technologies  into  advanced  pilots  for  exascale  systems.  The  pilots  will  adopt  a  co-design 
approach to bridge the gap between suppliers and users to define new architectures and better 
computational methods and algorithms adapted to real application needs. 

2.3 Main achievements of the EuroHPC JU in its first year of operations 
In 2018, the Impact Assessment (IA)4 and a study by the European Investment Bank (EIB) 29 
on financing supercomputing in Europe identified a range of obstacles to the development of 
a successful HPC ecosystem in Europe. The EuroHPC JU has already removed a number of 
these  obstacles,  bringing  substantial 
its 
establishment, as confirmed by the “Impact Assessment Study for Institutionalised European 
Partnerships  under  Horizon  Europe  -  Candidate  Institutionalised  European  Partnership  in 
High-Performance Computing (Final Report)”30.  

the  situation  previous 

improvement 

to 

to 

The  following  paragraphs  describe  the  main  achievements  of  the  JU  in  advancing  from  the 
baseline  situation  analysed  in  the  2017  Impact  Assessment  and  the  EIB  study  on  financing 
supercomputing, for simplicity referred to as “EuroHPC IA” and “EIB study”, respectively.  

1.  The  EuroHPC  JU  has  substantially  increased  the  level  and  quality  of  investments  in 

HPC at European level in a single and coordinated effort with Member Statesvii 

  The EuroHPC JU coordinates and pools EU and national investments  

Overall, the EuroHPC JU provides a powerful single legal framework for pooling the 
necessary EU, national and regional resources, mobilising public and private efforts at 
European  level  to  support  the  HPC  ecosystem.  All  the  Participating  States  provide 
strong  support  to  the  JU  and  contribute  to  its  success.  The  JU  has  now  become  the 
instrument  for  pooling  resources,  coordinating 
most  powerful  and  effective 
investments and promoting collaboration between the EU and the Participating States 
in organising specific actions, driven by an ambitious European HPC strategy.  

vii  The baseline, as defined in “EuroHPC IA” and the “EIB study”, is the following:  

  EuroHPC IA, “Problem driver number 1” (Public funding for HPC in EU/MS remains uncoordinated and 

insufficient to cope with the demand) 
“MS investments are insufficient and uncoordinated to acquire enough high-end HPC systems that satisfy 
the  demand…  No  MS  has  the  capabilities  to  develop  the  necessary  HPC  ecosystem  on  its  own  in  a 
competitive timeframe with respect to the USA, China or Japan…. When compared to current investments 
of the EU and MS, the gap with the USA can be estimated at least at EUR 700 million per year.” 

  EuroHPC IA, “Problem Nr 3” (Member States do not have a framework for joint procurement) 

“… (the current situation) does not cover the coordination of national programmes, nor joint investments 
for the procurement of systems, …. In Europe, the large fragmentation of HPC programmes and efforts, 
the  non-coordinated  activities  and  the  lack  of  a  common  procurement  framework  lead  to  a  waste  of 
resources....  Europe  thus  misses  the  opportunity  to  take  advantage  of  efficiency  gains  by  aligning  the 
strategies and pooling resources. 

  EIB  Study:  “Finding  2”  (Fragmentation  and  limited  coordination  at  the  EU  level  has  resulted  in  a 
suboptimal investment climate and an underinvestment in strategic HPC infrastructures in Europe):   
“…the majority of HPC centres tend to be standalone organisations with a close link to a local academic 
institution  or  are  embedded  in  a  research  cluster…  resulting  in  fragmentation  and  limited  coordination 
across  Europe…  Furthermore,  the  financing  for  large-scale  HPC  facilities  is  challenging  due  the  large 
amount  of  resources  required  and  the  need  for  long-term  and  sustained  financing  …  (leading  to) 
significant underinvestment in this strategically important sector in Europe.” 

12 

 
 
                                                 
The  EuroHPC  Research  and  Innovation  Advisory  Group  (RIAG)  draws  up  the 
strategic  R&I  agenda  of  the  JU  with  the  support  of  the  European  industry  players 
participating as Private Members of the JU (the ETP4HPC and BDVA Associations). 
This agenda reflects the global strategic developments in the field. 

  The EuroHPC JU has rationalised the implementation of national and EU investments 

and programmes  

At EU level, before the JU’s establishment, the Commission was using four different 
programmes  to  implement  HPC  activities:  FET,  LEIT-ICT  and  the  e-Infrastructures 
(Horizon  2020)  and  the  Connecting  Europe  Facility  (CEF).  EuroHPC  represents  a 
clear  improvement  to  that  situation:  by  integrating  all  HPC  activities  into  a  single 
instrument, it helped resolve the problem of fragmentation and lack of coordination of 
the Union’s HPC resources. 

At  national  level,  the  EuroHPC  JU  helps  rationalise  and  optimise  investments  and 
redefine  national  strategies  and  programmes  by  exploiting  synergies  and 
complementarities with the relevant Union’s actions and European priorities. 

  The EuroHPC JU has increased the overall HPC investments in Europe 

Regarding  the  overall  level  of  funding  in  HPC,  the  JU  has  initiated  so  far  an 
unprecedented investment in European advanced digital infrastructures, responding to 
the  need  identified  in  the  EIB  Study:  “Increase  financial  support  from  the  public 
sector  for  strategic  HPC  infrastructure  and  services  with  an  emphasis  on  improved 
coordination and a strong public value investment approach”.  

For the period 2019-2020 alone, the JU will mobilise public commitments of around 
EUR 1.1 billion, representing a net increase of nearly EUR 250 million per year at 
European level, compared with the situation before the creation of the EuroHPC JU.  
2.  By the end of 2020 EuroHPC will provide the EU with the best world supercomputersviii 

  World and EU supercomputing capabilities 

Europe was,  and still is,  a world leader in  HPC  applications, but  its supercomputing 
infrastructure  is  falling  behind  in  the  world  ranking.  A  widely  accepted  headline 
indicator of regional competitiveness in HPC is the number of systems in the “top-10” 
and “top-500” lists of world supercomputers31 in each world region.  

viii  The baseline, as defined in the “EuroHPC IA” and the “EIB study”, is the following: 

  EuroHPC IA, “Problem Nr 1” (The EU does not have the best supercomputers in the world…) 

Today, none of the 10 leading supercomputers in the world is located in the EU … Collectively,  the EU 
and  the  MS  are  significantly  under-investing  in  HPC  technology  supply  and  infrastructures  when 
compared to USA, China or Japan.” 

  EuroHPC IA, “Problem Nr 2” (Supercomputers available in Europe do not satisfy the demand) 

“Not only Europe does not have the best machines but it also cannot sufficiently satisfy the demand. … 
the  European  scientific  and  engineering  research  community  prefers  to  use  USA  supercomputing 
facilities  rather  than  PRACE….  Ultimately,  our  scientific  and  industrial  leadership  will  become 
dependent on the accessibility to the highest-end machines that are outside Europe.”  

13 

 
 
                                                 
Figure 2 - World top 500 supercomputers - regional share 

In June 2020, only two of the world’s top ten supercomputers were to be found in the 
Union,  ranking  sixth  and  ninthix,  compared  with  four  systems  in  2012.  The  current 
supercomputing power in the world top 500 supercomputers available in the Union is 
less than half of the US or China. Out of these top 500 systems, 79 are installed in EU 
Member States, as compared with 114 in the US and 226 in China. 

Figure 3 - Share of HPC systems in global top-10 per country 

With the acquisition of its supercomputing infrastructure planned for the second half 
of 2020, the EuroHPC JU will start to bridge the gap. For example, its three precursor-
to-exascale systems would be placed in the top-5 in the world, and its five petascale 
supercomputers will be among the top-50 – see Figure 4. 

Figure 4 - Computing power of world top 10 supercomputers 

ix   “HPC5” (ENI - IT) and “Marconi-100” (CINECA - IT), with peak performances of 51 and 29 petaflops 

14 

 
 
  
 
 
                                                 
EuroHPC  will  also  make  it  possible  to  address  the  first  issue  identified  in  the 
EuroHPC IA, namely a lack of investment in Europe in world-class supercomputers to 
address the digital divide across Europe with regard to access to available resources. 
The EuroHPC JU allows consortia of different Participating States to contribute to the 
acquisition  and  operation  of  the  supercomputers.  This  pooling  mechanism  gives 
Participating States the right to allocate part of the computing resources  proportional 
to  their  financial  contribution  to  national  priorities  and  users,  and  will  have  a  very 
important  effect  at  national  level:  it  will  give  national  users  of  consortia  countries  a 
direct access to world-class resources that would have never been possible otherwise. 

  The  EuroHPC  JU  will  have  an  enormous  effect  in  facilitating  access  to  the  best 

supercomputer resources in Europe  

EuroHPC will have a knock-on effect in the widening of HPC in countries that have 
never  had  “ownership”  of  such  computing  power.  In  total,  20  of  the  32  countries 
participating in the EuroHPC JU will be part of the consortia operating the centres. For 
some  Participating  States,  this  will  also  mean  hosting  or  enjoying  national  exclusive 
access  to  a “top-500” supercomputer  for the  first time ever  – resulting in a quantum 
leap in supercomputing knowledge for their national stakeholders.  

Figure 5 - Members of Consortia in EuroHPC JU supercomputers 

With the exception of the Czech Republic, the other four sites selected for EuroHPC 
petascale  computers  do  not  have  a  particular  track  record  of  hosting  “top-500”  HPC 
facilities. This underlines the value proposition of participation in the partnership for 
smaller  Member  States  –  they  can  reap  the  benefits  of  hosting  facilities  that  they 
would not otherwise have been likely to access. 

  The EuroHPC JU will dramatically increase the computing power supply for EU users 

The EuroHPC IA identified a shortage of supply of supercomputing infrastructures in 
Europe,  and  this  remains  the  case  today:  given  the  lack  of  top-performing  HPC 
machines  in  the  EU,  the  European  scientific  and  engineering  research  community 
prefers to apply for US supercomputing facilities (i.e. in the US Advanced Scientific 
Computing  Research  (ASCR)  Programme)32  rather  than  resources  in  PRACE.33 
Current  demand  for  HPC  infrastructure  and  services  in  the  Union  far  exceeds  the 

15 

 
 
 
supply  offered  by  public  HPC  centres  and  private  operators.  For  instance,  PRACE 
Tier-0x calls have an average oversubscription ratio of 3:1,34 and there is evidence that 
a  part  of  the  scientific  community  in  Europe,  especially  in  the  EU13,  does  not  have 
access  to  the  level  of  supercomputing  performance  that  they  need  for  research 
purposes. 

A  comparison  between  PRACE  and  its  US  counterpart,  ASCR,  shows  the  extent  to 
which European HPC facilities cannot satisfy the demand for them: ASCR awards ten 
times  more  projects  to  European  scientific  and  engineering  communities  than 
PRACExi. Even the five hosting PRACE members (Germany, France, Spain, Italy, and 
Switzerland)  obtained  more  projects  from  ASCR  than  the  maximum  PRACE  could 
offer per call. This is also true of some associated members of PRACE like Denmark 
and the UK that do not provide computing systems to PRACE. In conclusion, there is 
strong demand for HPC access in the EU that is not sufficiently satisfied by PRACE. 

The new computational capacities which the EuroHPC JU will provide will efficiently 
tackle  this  problem.  EuroHPC  will  multiply  by  eight  the  computing  power  (in 
petaflops) and by at least 10 times the available computing time currently offered by 
the PRACE Tier-0 top supercomputing systemsxii, meaning that many more users will 
have access to top HPC resources for European-level use.  

      Figure 6 - European computing power in 2020 (forecast) 

x   Tier-0 systems are world-class supercomputers accessible at European level through the PRACE pan-

European scheme for allocating HPC resources 

xi   The comparison is relevant since both programs have a similar allocation mechanism awarding one year or 
multi-year core hours. The number of awarded projects is based on the last available ASCR report for 2017.   
xii   The percentage of time dedicated for European use of the EuroHPC systems will vary between 50% of the 
pre-exascale systems and 35% of the petascale systems, whereas Tier-0 systems dedicate in average less than 
40% of their time to PRACE 

16 

 
 
 
                                                 
3.  EuroHPC will provide a European source of key technologiesxiii   

  The EuroHPC will change the landscape of the European supply chain ecosystem 

Compared to the baseline situation of the HPC technological supply chain described in 
the EuroHPC IA, the situation is stationary: Europe continues to consume around 30% 
of  the  world  HPC  resources,  but  European  vendors  hardly  get  between    5%  and  6% 
market share in the “top-500” systems (with ATOS as the most significant European 
vendor,  with  5.2%).  No  European  company  supplies  key  components  like  general 
processors or accelerators. 

EuroHPC will be in an excellent position to contribute to the EU’s digital autonomy in 
critical technologies by supporting ambitious actions to support the development of an 
excellent European HPC ecosystem capable of significantly increasing the production 
of innovative technology. Europe’s investments  and strengths in technology building 
blocksxiv need now to be integrated in the next generation of supercomputers to help 
European industry become a leading technology supplier and reinforce its position as a 
world-leading user of HPC.  

An opportunity for this to happen is the EuroHPC JU’s planned 2020 calls, which will 
fund the next phase of the European  Processor  Initiative (EPI) and the integration of 
European  technologies  in  advanced  pilots  for  exascale  computing.  The  transition  to 
exascale  computing  is  already  announced  in  the  present  EuroHPC  JU  Regulation.  It 
represents  the  opportunity  for  Europe’s  supply  industry  to  leverage  on  technologies 
across the computing continuum.  

  Establishing a world level playing field in HPC 

The EuroHPC IA summarises the situation that HPC system vendors are facing in the 
market as follows: there is no level playing field in the HPC market; and procurement 

xiii  The baseline, as defined in the “EuroHPC IA” and the “EIB study”, is the following:   

  EuroHPC IA, “Problem Nr 1” (.. (the EU) is entirely dependent on non-European HPC supply chains with 
the increasing risk of not having access to latest strategic technology even if resources were available) 
“Our HPC technology supply chain is still weak, with an insignificant level of integration of European 
technologies  into  operational  HPC  machines…  EU  depends  on  other  regions  for  the  supply  of  critical 
technology for its HPC infrastructure. EU risks getting technologically deprived of strategic know-how 
for innovation and competitiveness…” 

  EuroHPC IA, Problem Nr 4 (The European HPC technology supply chain is weak and the integration of 

European technologies into operational HPC machines remains insignificant) 
“(In 2017) Europe consumes about 29% of HPC resources worldwide, but the EU industry provides only 
~5% of such resources worldwide….In addition, close to one fifth of the top 500 HPC systems are located 
in the EU, and out of these, ~20% are provided by EU vendors (oscillating between 20% and 25% over 
the last years)” 

  EuroHPC  IA,  Problem  Driver  Nr  2  (European  HPC  system  vendors  face  stiff  competition  from  large 

foreign corporations still to solve) 
On the global market, the European suppliers face unequal treatment on public procurement. The USA 
and China restrict the development and procurement of the high-end machines to domestic suppliers…. 

xiv  Examples  of  such  technology  building  blocks  include:  power-efficient  nanoelectronics,  interconnect  and 
processor designs, middleware solutions, parallel programing and computing resource optimisation solutions, 
scientific and industrial codes, etc.). 

17 

 
 
 
                                                 
for the development and acquisition of the high-end machines is restricted to domestic 
suppliers for national security reasons.4 

To improve this situation, the Governing Board of the EuroHPC JU has enforced the 
mandatory use of Article 30.335 of the Horizon 2020 Model Grant Agreement in all the 
R&I  actions  it supports, in  order to  avoid  transfers of critical  intellectual property to 
third countries. The EuroHPC JU retains the right to object to a transfer of ownership 
or  the  exclusive  licensing  of  results  if  it  is  to  a  third  party  established  in  a  non-EU 
country  not  associated  with  Horizon  2020,  if  the  JU  considers  that  the  transfer  or 
licence  is  not  in  line  with  EU  interests  regarding  competitiveness  or  is  inconsistent 
with ethical principles or security considerations. The EuroHPC JU may also consider 
using  additional  exploitation  obligations  (for  example,  that  the  first  exploitation  of  a 
given technology has to be in the Union) as provided by Article 28.1 of the Horizon 
2020 Model Grant Agreement. 

4.  EuroHPC will increase and widen the use of HPC in the EUxv 

  Widening HPC use 

Each  industrial  sector  must  understand  the  potential  of  HPC  before  specialised  HPC 
applications  can  be  developed  and  exploited.  Too  often  HPC  use  still  requires 
advanced knowledge about the sector and highly specialised technology skills. This is 
particularly relevant for SMEs, as pointed out in the EIB Study: 

“While data-driven high-tech SMEs are rapidly engaging in the adoption of HPC into 
their  businesses,  a  large  number  of  more  ‘traditional’  SMEs  (such  as  engineering 
SMEs  manufacturing  components  for  large  automakers)  still  lack  awareness  of  the 
important opportunities HPC would provide to their businesses.”29 
In  its  R&I  2019  Call,25  the  EuroHPC  JU  supports  actions  that  directly  address  this 
situation:  establishing  HPC  competence  centres,  enabling  industrial  applications  and 
codes  to  optimise  the  use  of  HPC  and  stimulating  the  innovation  potential  for 
manufacturing and engineering SMEs, complemented by a Horizon 2020 call for new 
HPC Centres of Excellence.27 These actions respond to a key recommendation of the 
EIB  Study:  to  “strengthen  the  uptake  by  HPC  users,  in  particular  for  commercial 
applications  by  industry,  SMEs,  and  innovative  companies  and  start-ups  by 
strengthening the role of HPC intermediaries via public support.” 

–  EuroHPC Competence Centres will be established in all Member States in 2020. 
Their aim will be to increase the use and expertise in HPC technologies, and help 

xv The baseline, as defined in the “EuroHPC IA” and the “EIB study”, is the following:   

  EIB study, Finding 1 (Demand for HPC capabilities is rapidly increasing in key sectors of the European 
economy,  such  as  aerospace,  automotive,  energy,  manufacturing  and  financial  services,  while  Europe’s 
more  ‘traditional’  SMEs  are  lagging  behind)  “The  rapid  growth  of  the  data  economy  is  leading  to  a 
significant  increase  in  demand  for  HPC  infrastructure  and  services  (including  commercial  uses)… 
However,  an  ongoing  critical  challenge  is  the  need  to  better  support  researchers  and  entrepreneurs  in 
appropriating  this  technology  in  line  with  their  needs  and  adopting  it  accordance  with  their 
requirements…  there  is  a  gap  in  HPC  adoption  and  usage  between  large  industry  players  and  more 
‘traditional’ SMEs.” 

  EuroHPC  IA,  the  main  consequence  for  Science  and  Industry  of  the  low  use  of  supercomputers  is  the 
“Loss of innovation / stiff competition to access to few available resources (particularly for SMEs))” 

18 

 
 
                                                 
 
bridge the digital skills gap. The Centres will act locally, to provide knowledge and 
computing  services  supporting  the  real  needs  of  businesses,  in  particular  SMEs 
that do not  have the in-house resources to  profit from  the new technologies.  The 
Centres will be networked together and will be part of the pan-European network 
of current and future Digital Innovation Hubs36 being established across the Union. 
This  networking  will  help  exchange  best  practices,  making  the  resources  and 
expertise of the Competence Centres available across the Union.   

–  Stimulating  manufacturing  and  engineering  SMEs  to improve  their  innovation 
potential by using advanced HPC services. The aim is to widen the HPC user base 
by  attracting  new  users  in  different  application  domains,  and  to  provide  an 
effective mechanism for the inclusion of innovative, agile SMEs by lowering the 
barriers  for  small  players  to  enter  the  market  and  exploit  new  business 
opportunities. This EuroHPC action will build on the Fortissimo actions37, which 
were highly successful in attracting new SME users to advanced cloud-based HPC 
solutions  based  on  modelling,  simulation  and/or  high  performance  data  analytics 
(HPDA). 

 

Industrial and commercial use of HPC infrastructures 

According  to  the  EIB  study,  there  is  a  need  for  developing  commercially  oriented 
business models based on secure and flexible HPC services and data infrastructures, as 
shown by growing interest from European industry.  

Today, the European HPC landscape is driven by the public sector, in both usage and 
financing. Most of the high-end HPC capacity and use (over 90% of operating time) is 
located  at  and  allocated  to  universities  or  academic  research  centres.  The  remaining 
10%  is  available  for  commercial  use  or  with  HPC  end  users.  However,  HPC  is  of 
strategic importance for companies, and HPC use involves company data that must be 
stored and treated under strict security conditions and respecting privacy regulations. 
These conditions cannot be easily met by publicly owned/operated HPC centres. 

The  EuroHPC  JU  is  addressing  this  as  follows:  as  soon  as  the  JU’s  supercomputers 
become available (by the end of 2020), they will be accessible to industry players for 
publicly  funded  R&I  purposes.  In  addition,  the  EuroHPC  JU  Regulation  explicitly 
stipulates that up to 20% of the Union's access  time of the EuroHPC systems can be 
allocated for commercial purposes, following a pay-per-use service, based on market 
prices.  

On the advice of INFRAG, its Infrastructure Advisory Group, the EuroHPC JU is now 
working  on  how  to  define  and  provide  these  access  conditions  to  European  industry 
players  by  noting  that  the  EuroHPC  supercomputers  will  be  at  least  ten  times  more 
powerful than any industrial system installed in Europe.xvi The JU will also investigate 
the  necessary  usability,  trust,  and  security  needs  of  industrial  users.  As  a  result, 
EuroHPC will play a decisive role in spreading and substantially increasing HPC use 
by key EU industry players, creating a demand for more HPC resources for industrial 
use,  and  setting  the  foundations  for  a  strategic  collaboration  between  public  and 
private HPC stakeholders. 

xvi  The most powerful industrial system in the EU in November 2019 is Pangea III (Total company, France) 

19 

 
 
                                                 
2.4 The EuroHPC strategy and its impact on the HPC value chain 

Horizon  2020  is  the  main  EU  programme  to  have  supported  the  Union’s  efforts  in 
implementing the European HPC strategy and in developing the European HPC value chain. 
Up to 2018, around EUR 430 million was committed to R&I activities, including technology 
projects (EUR 313 million), Centres of Excellence (EUR 118 million) and Coordination and 
Support  actions  (EUR  10  million).  The  EuroHPC  JU  is  implementing  the  support  from 
Horizon 2020 for 2019-2020. 

The impact of this support to the European HPC value chain has been analysed by European 
stakeholders38.  The  main  conclusions  are  that  Horizon  2020  has  contributed  to  achieving 
significant  impacts  on  the  European  HPC  value  chain.  It  has  supported  the  development  of 
key technology results (most of them up to TRL 5-6-7xvii) and applications and contributed to 
creating a stronger and more connected HPC ecosystem.  

1.  The European HPC value chain  

The  production  and  operation  of  HPC  systems  involve  a  complex  value  chain  of  system 
hardware, system and application development software, applications, and transversal aspects. 

  HPC system hardware: Horizon 2020 has supported key projects in the system hardware 
value  chain:  EPI26  to  reposition  Europe  in  a  processor  market  dominated  by  US 
technologies,  Exanode39  for  chip  integration.  Exanest40,  EuroExa41  and  Mango42  for 
interconnects, and cooling solutions industrialised by SMEs (such as Iceotope or Submer). 
In  addition,  the  suite  of  Montblanc43  projects  are  world-leading  contributors  to  the 
emergence of ARM processor HPC systems and have achieved key results in FPGAsxviii 
that have been commercialised by some SMEs (such as Maxeler).  

  HPC  system  and  application  development  software:  The  contribution  of  the  Horizon 
2020 projects is very diverse. Domains in which significant results are expected include a 
software stack for ARM-based processors systems, software for efficient use of the new 
levels of the storage hierarchy, resource and energy management tools, scientific libraries, 
domain specific languages for machine learning applications, programming environments 
for heterogeneous systems (CPU, GPU and FPGA), and visualization tools for interactive 
HPC.  Most  of  the  SMEs  funded  by  the  projects  (e.g.,  Maxeler,  Appentra,  Arctur, 
Synelexis and Kitware) have been effective in bringing project results to the market. 

  HPC  applications:  This  part  of  the  value  chain  is  of  utmost  importance  in  Europe.  10 
Centres of Excellence (CoEs) in HPC applications have been established in Horizon 2020. 
They have delivered results such as a weather and climate simulation framework ready for 
exascale systems, new advances in codes for material science, life science and carbon-free 
energy, and a methodology to assess and improve the performances of HPC codes. CoEs 
have the task to promote HPC research applications within industry. Large scale industrial 
pilots are supported in the areas of digital twins, health, precision agriculture and farming, 
or finance and insurance.  Projects funded by the CEF-Telecom programme use HPC to 
support  objectives  in  important  application  areas  such  as  smart  agriculture  and  forestry 

xvii  Technology  readiness  levels  (TRL)  is  a  method  for  estimating  the maturity of  technologies,  from  level  1 

(basic principles) to level 9 (actual system proven through successful operations) 

xviii  

Field-programmable gate array (FPGA) is an integrated circuit that can be programmed in the field after 

manufacture.  

20 

 
 
                                                 
evolution  and  fire  control,  air  quality  and  pollution,  atmospheric,  marine  and  earth 
observation, or cultural heritage in the EU.  

Besides  the  specific  actions  above,  funded  projects  have  also  impacted  the  application 
value chain: almost all the project consortia include application-oriented partners. In total 
more than 100 codes have benefited from the Horizon 2020 support. In addition, Horizon 
2020 funding has contributed to developing tailored solutions for more than 100 European 
SMEs,  increasing  their  innovation  potential.  This  funding  made  it  possible  to  raise 
awareness of HPC and AI and provide high-end computing capabilities to SMEs through 
the  PRACE  SHAPE44  initiative,  and  to  provide  SMEs  with  cloud-based  HPC  services 
through Fortissimo’s marketplace.37 

  Transversal  aspects:  The  most  important  transversal  aspect  in  Horizon  2020  was 
training,  provided  mainly  by  Centres  of  Excellence  and  PRACE  with  a  total  estimated 
value  of  around  EUR  23  million.  Both  domain  specific  training  and  training  on  general 
HPC topics was provided to more than 13 000 people. 

2.  Conclusions 

Horizon  2020  and  CEF  funding  have  already  produced  very  good  results  in  the  different 
segments of the value chain. However, the impact has not yet changed the worldwide market 
position of the European players and has not reached some parts of the value chain, such as 
the industrial HPC application sector. This is because the investment has not been substantial 
enough  to  impact  the  complete  R&D  value  chain  (except  for  investments  in  the  European 
Processor Initiative).  

Projects  are  not  managing  to  transform  the  day  to  day  use  of  HPC,  as  the  gap  between 
developed technologies (TRLs 5-7) and their use in production environments is still big. The 
majority of project partners are from research organizations (75% of the total funding of the 
FET projects), whose mainspring is not industrialisation of results achieved. The addition of 
projects targeting the TRL 6/7-9 gap and a more programme-based approach should help to 
maximise the impact of the future investments. 

Enhanced and sustained training efforts will also be a major factor in fully exploiting not only 
the  next  EuroHPC-funded  pre-exascale  and  exascale  supercomputers  but  also  future 
computing  generations.  Moving  from  simulation-centric  HPC  to  integrating  HPC  in  a  full 
continuum of IT infrastructure, from edge to HPC, is a major challenge. This would require to 
develop a strong relationship between the HPC community with other ecosystems such as big 
data,  AI  and  Internet  of  Things  (IoT).  Here  Europe  can  be  a  worldwide  leader  if  the 
momentum created by Horizon 2020 continues. 

2.5 Lessons learnt from the EuroHPC JU governance and administration 
The  EuroHPC  JU  has  already  acquired  solid  working  experience,xix  with  extensive 
discussions  of the stakeholders on the  governance, administration and other operational  and 

xix  Examples  include:  The  13  meetings  of  the  EuroHPC  JU  Governing  Board  with  the  regular  participation  of 
Delegates from the European Commission and the 32 Participating States; the JU’s advisory groups (RIAG 
and INFRAG) - these held already numerous meetings and were supported by the active involvement of the 
two  Private  Members  (ETP4HPC  and  BDVA);  the  selection  of  the  8  hosting  sites  and  the  launch  of 
procurement of the 8 EuroHPC supercomputers; and, the launch of the JU’s 2019 and 2020 calls. 

21 

 
 
                                                 
implementation  aspects  from  which  the  following  main  lessons  learnt  so  far  can  be 
summarised as follows: 

  Simplification of the co-funding scheme: The combination of EU and national funds 
in  the  different  EuroHPC  activities  needs  to  be  simplified  and  optimised. 
Recommendations include a single set of eligibility criteria for participation (instead 
of 32 different national eligibility criteria); implementation of central management of 
all financial contributions (except in duly justified cases), in line with Article 8(1)(c) 
of  the  proposed  Regulation  establishing  Horizon  Europexx;  and  flexibility  in 
introducing different percentages of EU and national funding to fund participants in 
R&I activities.   

  More  flexibility 

in  defining  the  acquisition  time  and  technology  of  new 
supercomputing systems e.g., by avoiding fixing in the Regulation the acquisition dates 
of future EuroHPC systems requiring a particular performance level, since this may clash 
with  market  reality  of  available  technologies.  The  performance  could  be  set  when  a 
decision  is  taken  for  the  acquisition.  In  addition,  the  expected  “performance”  of  the 
supercomputers  should  be  flexibly  defined,  for  example  as  a  combination  of  computing 
power,  application  performance  gains,  expected  ranking  in  world-class  supercomputing 
categories, etc.  

  More  flexibility  in  the  resource  allocation  of  the  EuroHPC  systems:  By  the  end  of 
2020,  the  available  computing  power  at  the  Union  level  will  increase  almost  eight-fold. 
There  will  then  be  a  need  for  more  choice  and  flexibility  when  allocating  the  EuroHPC 
computing resources, notably by considering new user requirements taking advantage of 
novel  computing  architectures  (see  next  Chapter).  Currently,  on  the  advice  of  INFRAG, 
the  EuroHPC  JU  Governing  Board  is  drawing  up  more  flexible  resource  allocation 
policies  and  priority  allocation.  Criteria  under  consideration  include  different  access 
policies  for  scientific  and  industrial  players;  direct  access  possibilities  for  key  European 
projects and initiatives without submitting a call for expression of interest (e.g., for HPC 
Centres of Excellence, HPC Competence Centres or other key EuroHPC projects), priority 
access for crisis management situations, etc. 

  Well-defined  access  policies  for  the  industrial/commercial  use  of  the  EuroHPC 
infrastructure  that  would  enable  the  full  exploitation  of  the  EuroHPC  capabilities  in 
either  pre-competitive  research  access,  or  in  commercial  terms  of  use.  In  addition,  they 
would  need  to  consider  an  enhanced  quality  of  service,  and  the  usability,  trust,  and 
security needs that industrial users require to access secure HPC resources. 

  A  clearer  framework  for  collaboration  with  PRACE  and  GEANT.  Specific 
arrangements  may  need  to  be  established  with  PRACE  for  the  tasks  related  to  the 
allocation of the access time to the JU’s systems, for training and dissemination activities, 
and for developing a fully cloudified and federated HPC service and data infrastructure in 
Europe.  Similarly,  the  EuroHPC  JU  could  make  use  of  the  experience  of  GEANT  for 
procuring dedicated connectivity for the EuroHPC supercomputers.  

  A  better  definition  of  the  different  contributions  to  the  activities  of  EuroHPC.  For 
example,  there  is  a  need  to  further  define  the  in-kind  contributions  of  the  Participating 

xx  Council  of  the  European  Union  (7942/19  COR  1  of  29  March  2019)  -  General  Partial  Agreement  text  on 

Horizon-Europe 9, Art 8.1.(c) reflecting the common understanding between Council and Parliament 

22 

 
 
                                                 
States and of the Private Members to the EuroHPC JU; and to better define the costs that 
EuroHPC can/cannot support for the acquisition and operations of supercomputers. 

  More flexibility in the contribution of Private Members and other private actors to 
the  activities  of  the  EuroHPC  JU,  notably  by  including  novel  forms  of  cooperation,  for 
example co-funding specific HPC infrastructure for industrial use. 

3.  HPC in a fast evolving environment 

This chapter identifies the evolution of key market, socio-economic and technological drivers 
that will affect the way HPC is developing world-wide and in the Union in the next 5-7 years. 
Part of this evolution is provided in the Vision Paper prepared by the EuroHPC JU Industrial 
and  Scientific  Advisory  Board45.  The  chapter  analyses  in  particular  the  following  main 
drivers: 

  The increasing importance of HPC for a wide range of applications 

  The HPC market drivers 

  The evolution of the user requirements (from science and industry)  

  The convergence of HPC with AI and related technologies 

  The evolution of supercomputing technologies  

  New computing paradigms: Neuromorphic and Quantum computing  

  The training and skills required in the next decade 

  The new Political Guidelines for the period 2020-2025 

3.1 The increasing importance of HPC for a wide range of applications  

During the last decade,  political  leaders in  the developed countries have recognized the key 
importance  of  HPC-powered  applications  to  help  transform  their  economies  and  societies.  
Mastering  HPC  applications  has  become  indispensable  to  advancing  science,  boosting 
industrial  competitiveness,  improving  the  quality  of  daily  life  for  citizens,  and  reinforcing 
national security and technological autonomy. 

Excellence  in  the  development  and  use  of  applications  exploiting  the  supercomputing 
capabilities will be a major global driver for HPC. More than 800 HPC applications are used 
across all scientific fields, branches of government and virtually all industries and sectors, and 
Europe has traditionally been a world leader in this domain4. Several of the most used HPC 
codes are European (e.g. FOAM for computational fluid dynamics, GROMACS for molecular 
dynamics, VASP  and  Quantum  Expresso  for  quantum  materials  modelling,  Simulia 
Abaqus for  finite  element  analysis and computer-aided  engineering).  European  companies 
have pioneered the industrial use of HPC applications such as crash test codes in automotive, 
in-silico  drug  design  and  testing  in  pharma,  or  computer  aided  design  in  aerospace.  The 
importance of HPC applications as a key driver can be illustrated as follows:  

HPC and the data revolution  

The convergence of HPC, Artificial Intelligence (including Machine and Deep Learning), big 
data and high performance data analytics (HPDA), and Cloud are already and will continue to 
be the main innovation drivers in the “data revolution”, creating entirely new possibilities for 

23 

 
 
HPC-powered applications to extract useful and usable knowledge from the huge amount of 
raw data produced every day. HPC are increasingly becoming the “engine” that powers such 
data revolution, and a key element to fulfil the ambition of putting Europe in the driving seat 
of  the  global  data  economy.  Section  3.4  analyses  in  further  detail  the  convergence  of  HPC 
with Artificial Intelligence and related technologies.  

HPC and industry’s innovation potential 

HPC is a mainstream technology for the digital transformation of European industry. The use 
of  HPC  applications  and  tools  is  expanding  to  all  industries  as  it  becomes  more  accessible 
with  today's  and  future  broadband  networks.  HPC  applications  have  traditionally  enabled 
industrial sectors that are “computationally aware” like manufacturing to move up into higher 
value products and services. In particular, the use of HPC applications and services over the 
cloud will make it significantly easier for SMEs that do not have the financial means to invest 
in their in-house HPC development to develop and produce better products and services. 

HPC and scientific leadership 

HPC  is  now  firmly  established  as  the  third  pillar  of  modern  research,  alongside  theory  and 
experimentation. HPC applications have become an essential component in nearly every field 
of  scientific  research,  thanks  to  steadily  increasing  computing  power  and  widespread 
availability of HPC infrastructure, in particular since the 1990s. 

The  applications  of  HPC  in  science  are  countless:  fundamental  physics,  advancing  the 
frontiers  of  knowledge  of  matter  or  exploring  the  universe;  in  material  sciences,  designing 
new  critical  components  for  the  pharmaceutical  or  energy  sectors;  in  fluid  dynamics  and 
adaptive control problems for the design of airplanes or planning of smart cities; in modelling 
the atmospheric and oceanic phenomena at planetary level, etc.  It is probably in the field of 
life sciences and medicine where the tremendous impact of bioinformatics is very visible, for 
example  in  understanding  the  generation  and  evolution  of  epidemics  and  diseases  and  their 
early detection and treatment.  

Supercomputers  will  be  essential  for  the  success  of  the  European  “1+  Million  Genomes” 
initiative launched in 201846 aiming to creating a data space with access to at least 1 million 
sequenced genomes in the EU by 2022. Supercomputers will make possible for example the 
fast identification of genetic disease variants by processing billions of DNA sequences, or the 
screening of hundreds of billions of molecules in a few hours (rather than months or years) to 
identify potential candidates for a treatment or a vaccinexxi.  

HPC’s role in societal Challenges and policy making 

Citizens expect sustained improvements in their everyday life, while at the same time society 
is confronted with an increasing number of complex challenges – at the local urban and rural 
level  as  well  as  at  the  planetary  scale.  HPC  applications  are  a  strategic  resource  for  policy-
making,  helping  us  to  understand  our  ever-changing  world,  and  providing  a  much-needed 
evidence for designing efficient solutions in many of the global challenges.  

The  inter-disciplinary  nature  of  HPC  and  the  wide  range  of  applications  provides  policy 
makers  with  powerful  tools  in  critical  areas,  for  example:  Weather  and  Climate  change; 
Health, demographic change and wellbeing; Secure, clean and efficient energy; Smart, green 

xxi  The role of HPC applications in the COVID-19 global crisis is illustrated in Annex IV of this document. 

24 

 
 
                                                 
and integrated urban planning; Food security, sustainable agriculture, marine research and the 
bio-economy; or crisis management. xxi  

HPC’s role in the Union’s technological autonomy and security 

Supercomputers are essential for national security, defence and technological autonomy. They 
are  already  used  to  increase  cyber-security  and  in  the  fight  against  cyber-criminality,  in 
particular  for  the  protection  of  critical  infrastructures.  The  exponential  rise  of  the  economic 
losses associated to cybercrime (expected to reach EUR 5.4 trillion by 2021) reveals the need 
for developing secure applications and infrastructures that can anticipate and promptly react 
to an ever increasing menace.  

In cyber-security, HPC-powered applications will unlock the power of security tools thanks to 
their  capability  to  speed  up  the  AI-  and  machine  learning  (ML)-driven  complex  software. 
Hybrid techniques combining HPC and AI (in particular ML techniques) will increasingly be 
used  for  a  more  effective  threat  analysis  and  security  event  correlation,  contributing  to 
developing  self-healing  and  self-adaptive  cyber-security  systems:  detecting  strange  systems 
behaviour, insider threats and electronic fraud; detecting and fighting very early cyber-attack 
patterns (in a matter of few hours, instead of a few days) or potential misuse of systems; or 
taking automated and immediate actions even before hostile events occur. 

HPC  applications  in  combination  with  AI  will  be  a  game  changer  in  defence  and  security. 
Both  the  US  and  China  have  already  linked  closely  HPC  and  AI  developments  in  their 
defence  programmes.  The  US  President  Trump's  executive  order  on  Maintaining  American 
Leadership  in  Artificial  Intelligence47  makes  explicit  the  HPC-AI  link,  asking  his 
administration  to  prioritise  the  allocation  of  high-performance  computing  resources  for  AI-
related applications. 

3.2 HPC Market drivers  
The impact of HPC in the most developed economies of the world is impressive.xxii HPC has a 
growing contribution to the digitisation of critical industrial sectors that account for c. 53% of 
the Union’s GDP. Investments in HPC have shown particularly strong growth rates in recent 
years.  The  overall  HPC  market  is  expected  to  reach  EUR  39.6  billion  in  2023,  including 
expenditure in HPC servers, storage, software and technical support. In particular, expenditure 
in  HPC  servers  will  grow  from  EUR  12.33  billion  in  2018  to  EUR  17.9  billion  in  2023. 
Europe  maintains  a  relatively  constant  share  of  around  one-quarter  (c.  26%)  of  the  overall 
spending in all categories of HPC systems, while the USA continues as world leader in HPC 
investments. The main market developments can be summarised as follows: 

Strategic Investments in HPC  

  Return  on  investments  (ROI)  on  HPC  is  yielding  excellent  returns  in  the  EU:  on 
averagexxiii, every Euro invested in 2018 returned EUR 43.2 in profits or costs savings and 
EUR 260 in revenues. 

xxii  The  data  source  in  this  section  is  Hyperion  Research  2019  and  all  figures  and  sources  of  the  market  data 

provided in this section can be found in Annex I of this document, unless otherwise indicated. 

xxiii This includes public and private investments 

25 

 
 
                                                 
  Spending levels in the strategically important high-end market of systems over EUR 2.2 
million, are an important measure of HPC leadership. The current situation of the EU is 
not very satisfactoryxxiv, amounting to less than one third of the US and less than half of 
China supercomputing power in the world top-500 supercomputers.  

The exascale race and the ICT market 

  Exascale  performance  is  now  driving  investments  in  the  high-end  segment  of 
supercomputers.  Between  2020  and  2025,  the  global  spending  on  pre-  and  full-exascale 
supercomputers is expected to total about EUR 8 billion.  

  Advances in exascale HPC technologies will affect a market worth EUR 1 trillion, out of 
the  EUR  5  trillion  broader  ICT  market.  For  example,  low-power  processors  and 
accelerators for high-end computing will drive developments in technologies like Internet 
of Things (IoT), cybersecurity, AI, robotics and augmented and virtual reality. 

  US  vendors  have  almost  100%  of  the  world-wide  processor  market,  with  Intel  holding 
more than 95% in several categories of processors (CPU, GPU, etc.).xxv In the HPC sector, 
Intel’s share is lower, and around 95% of accelerators in the top 500 supercomputers are 
from NVIDIA. 

  The  race  to  exascale  and  the  convergence  of  HPC  with  AI  and  cloud  technologies  is 
changing  the  market,  putting  more  emphasis  on  low-power  processors,  accelerators  and 
GPGPUs  computing  in  data  servers,  which  fosters  the  use  of  ARM-based  technologies 
and allows US companies like AMD and NVIDIA to get an increasing market share.  

 

In the “top-500”, Chinese companies sell around 65% of the systems. Chinese indigenous 
processors  are  present  in  only  a  few  of  those  systems,  but  it  is  expected  that  Chinese 
technology  for  the  exascale  supercomputers  will  likely  enter  the  market  in  the  next  few 
years. 

  Solutions based on open-hardware (in particular RISC-Vxxvi) are gaining momentum as a 
credible alternative to the proprietary solutions for processors and accelerators across the 
computing continuum. Any company can use RISC-V without any fear of losing access in 
the  future  (for  instance  due  to  commercial  bans  on  technology  exports).  RISC-V  will 
create opportunities for non-US companies to break the almost monopoly situation in chip 
design. (e.g., European RISC-V accelerators in the EPI project and other activities). 

European HPC technology supply and market 

  On HPC supply (all segments), the US was the world leader in 2018 with 67% of global 
HPC sales, followed by China (16.2%), Japan (3.5%) and the EU (c. 1.1%). No European 
company supplies key components like general processors or accelerators. 

  Participation of EU vendors in the global HPC market is still weak. Out of all “top-500” 
supercomputers, only 28 (5.6%) are supplied by EU manufacturers. 26 were supplied by 

xxiv This does not take into account the planned acquisition of EuroHPC JU in 2020 that will be visible in 2021. 
xxv  CPU:  Central  processor  Unit;  GPU:  Graphic  Processor  Unit,  GPGPU:  General-purpose  computing  on 

graphics processing units. 

xxvi  RISC-V  is  an  open-source  hardware  instruction  set architecture based  on  reduced  instruction  set  computer 

principles 

26 

 
 
                                                 
one  main  EU  vendor  (Bull-Atos),  with  19  of  these  26  supercomputers  purchased  by 
clients in the EU and only seven clients globally. 

  Out of the 79 HPC systems in the top-500 list that are located in the EU, only 21 (26.5%) 
were supplied by European manufacturers. This means that almost 75% of the European 
HPC market is being supplied by non-EU manufacturers. 

The markets for HPC, Artificial Intelligence and Cloud are converging  

  Expenditure  related  to  the  use  of  HPDA  and  AI  will  be  the  fastest-growing  market 
segment for HPC. By 2023, the overall HPDA-AI market for HPC servers is expected to 
reach about EUR 5.76 billion, or about 32% of the EUR 18 billion worldwide market for 
HPC  server  systems  with  a  five-year  CAGR  of  15.4%.  The  subset  of  HPC-based  AI 
(machine/deep  learning  and  other)  is  expected  to  reach  EUR  2.43  billion  by  2023  for  a 
2018-2023 CAGR of 29.5%. 

  Worldwide spending on public cloud services and infrastructure is expected to reach EUR 
333 billion by 2022. The use of cloud for HPC workloads will jump substantially in the 
next few years, especially due to the growth in hybrid cloud deployments. Worldwide, the 
proportion  of  sites  exploiting  cloud  computing  to  address  parts  of  their  HPC  workloads 
has  grown  to  over  70%  in  2019,  helping  the  "democratisation  of  HPC".  By  2023, 
expenditure in cloud usage fees for HPC will reach around EUR 7.5 billion. 

3.3 Evolution of user requirements 

In the next 5-10 years, the requirements of private and public users for supercomputing and 
data  infrastructures  are  expected  to  evolve  at  a  rapid  pace.  An  analysis  carried  out  in  the 
Vision  Paper45  shows  that  users  require  a  computing  and  data  environment  allowing  a 
seamless  access  and  execution  of  complex  workflows  across  the  European  hyper-connected 
supercomputing  network.  This  environment  would  serve  interdisciplinary  user  communities 
using algorithms and data for generating knowledge. To this purpose, future supercomputing 
systems would need to provide many new computing and data applications and services, such 
as the following:  
  Data-driven  computingxxvii  and  compute-intensivexxviii  applications:  User  demand  is 
now  split  almost  equally  between  these  two  workload  types,  with  many  areas  utilising 
combinations of both, e.g. engineering.  

  Big-data  management:  Storage  and  I/O  requirements  are  expected  to  grow  even  faster 
than computing needs, in particular for data-driven and deep learning applications. These 
requirements would have to be coupled with provisioning of a large-scale end-to-end data 
e-infrastructure to collect, handle, analyse, visualise, and disseminate data.  

  Real-time  and  interactive  computing:  future  applications  that  depend  on  human 
intervention will require real-time and/or interactive computing, with examples including 
product design, medical applications, smart cities, smart grids and digital twins.xxix  

xxvii  Data-driven  computing  (e.g.  deep/machine  learning)  is  characterised  by  low  arithmetic  intensity,  irregular 
memory access, and fine grain recursive computations. Memory, network and data storage performance are 
the rate-limiting factors. 

xxviii Compute-intensive applications – e.g. material science – are characterised by high arithmetic intensity and 

regular memory access and have a rate limiting factor governed by floating-point throughput. 

27 

 
 
                                                 
  Urgent  computing  is  closely  related  to  real-time  and  interactive  computing,  the  main 
difference  being  its  lack  of  predictability.  Examples  are  typically  disaster  management 
and decision support in the event of e.g. floods, blackouts or traffic jams.  

The design of any future exascale and post-exascale supercomputer would need to be based 
on  a  co-design  approach  that  considers  enhanced  synergies  between  technology  suppliers, 
industrial and research users (in particular, advanced early adopters of new technologies) and 
algorithm and application developers. 

Evolution of industrial user requirements 

One of the critical success factors of HPC usage in industry is the capability to adapt to the 
specific industrial needs, which differ significantly from those of scientific users. 

Regarding  access  to  computing  resources,  the  main  differences  are  time  and  access 
procedures,  quality  and  type  of  services,  security  and  data  protection,  and  intellectual 
property: Academic users have longer research timescales, usually months or years. They can 
expect access decisions months after applying. In stark contrast, industrial users expect short 
access  time  to  computing  resources  to  reduce  lead-time  (from  the  demand  to  the  final 
delivery), with access to be primarily provided through the cloud. They also expect flexibility 
for adaptation to small changes, support to access configuration and/or set-up, and dedicated 
“services” and commodity for managing peaks of computer demand.  

the 

Industry  also  requires  intellectual  property  protection  for  the  results  and,  most  importantly, 
data  security  and  confidentiality.  This  concerns  the  secure  management  of  the  whole  data 
lifecycle:  from 
the 
computing/simulation process and the final result. Finally, industry players require guarantees 
of  safe  access  to  supercomputing  capabilities  when  developing  new  industrial  capabilities 
based on confidential studies.  
Some additional points identified in the Vision Paper45 are the following: 

intermediate  datasets  produced  during 

initial  datasets, 

to 

  Large companies have a unique role in the HPC ecosystem, as they purchase many of the 
world top-500 computers. They are generally already involved in HPC and collaborate in 
many areas with public research. Many of them are already accessing supercomputers of 
petaflop  performance  and  their  main  requirement  is  for  a  flexible,  competitive  system 
tailored to their expected use.  

  SMEs: Most European SMEs (and start-ups) are just moving to numerical simulation and 
data analytics. They generally need support, training and coaching to switch into the new 
HPC-powered world, with specific structures and activities.  

For  all industrial players there is  an  urgent  need  to  adapt  software codes  to  new computing 
architectures.  In  some  cases  this  can  be  difficult  due  to  certification  issues  (e.g.  airplane 
simulations). Industry also needs to develop innovative applications capable of exploiting not 
only the new architectures but  also  new paradigms (in particular AI-based). An example of 
the radical transformative role of HPC is digital twins.  

xxix  Digital  twins  are  exact  digital  replica  of  physical  entities,  products  and  constructions  that  reflect  the  static 
properties  as  well  as  the  evolving  behaviour  –  for  more,  see  section  “HPC  and  industry’s  innovation 
potential” in Annex 3. 

28 

 
 
                                                                                                                                                         
Industry  and  digital  twins:  A  new  generation  of  digital  twins  requires  the  powerful,  agile 
computing  capabilities  provided  by  HPC  to  facilitate  global  mobility  and  collaboration, 
combining  different  technologies  such  as  mixed  reality  tools,  cloud  rendering,  real-time 
simulation and analysis, IoT and deep learning/AI. New HPC-powered digital twins are able 
to  significantly  accelerate  product  development  and  manufacturing  processes,  by  generating 
digital  representations  of  their  end-to-end  business  processes  while  providing  new  ways  of 
collaborating simultaneously in the virtual and physical world. 

Finally, one of the biggest barriers that industry users face to efficient uptake and use of HPC 
is  the  need  for  wide  outreach  and  dissemination  of  the  concrete  benefits  that  HPC 
technologies  can  bring  to  them.  Entrepreneurs  will  be  encouraged  to  invest  into  HPC  if 
demonstrated  with  successful  business  plans,  innovations,  etc.  A  proactive  engagement  at 
local, regional and EU level will have to be undertaken to effectively engage with individual 
enterprises,  industrial  hubs,  and  SME  networks  and  associations  and,  in  particular,  the 
network of Digital Innovation Hubs and the Enterprise Europe Network.48  

In conclusion, industry users have specific usability, trust, and security requirements and need 
secure HPC resources and HPC-powered platforms for industrial innovation. Any future HPC 
initiative should address the following: specific access portals (e.g. cloud-based access), easy 
to-use  tools  (e.g.  for  big  data  analytics),  secure  application  workflows  between  industry 
premises  and  a  supercomputer,  an  appropriate  high-bandwidth  network  infrastructure  in  all 
European  countries,  etc.  An  important  aspect  is  the  certification  of  HPC  centres  as  reliable 
partners for industry, covering the aspects of usability, trust and security. 

3.4 The convergence of HPC with AI 

The convergence of HPC and Artificial Intelligence (AI) is critical for applications that rely 
on big data and high performance data analytics (HPDA). Exascale computing in combination 
with AI will have an enormous impact on the way computing is done.  

By 2018, the amount of computational power used to train the largest AI models had doubled 
every 3.4 months since 2012.49 AI and HPC are by their nature synergetic: for example, HPC 
simulations  generate  huge  amounts  of  data  and  AI  techniques  can  make  sense  of  it. 
Conversely,  HPC  can  be  used  to  explain  and  understand  AI  methods,  building  trust  in  the 
decisions made by AI. Annexes I and II present more details on key synergies and the market 
evidence on the convergence of these two technologies.  

One of the factors facilitating this convergence is the need to deal with the explosion of data. 
Besides  the  general  growth  of  available  data  in  the  digital  universe  (e.g.  more  than  460 
exabytes, i.e., 1018 bytes, will be generated every day by 2025)50, some key applications will 
require  both  extreme-scale  computing  capabilities  and  AI-techniques  to  handle  the  huge 
volumes of data. The following examples illustrate the magnitude of the challenge: 

Square Kilometre Array (SKA):  the data production of SKA is estimated at 11 exabytes 
daily,  i.e.  the  same  amount  of  data  in  a  day  as  the  entire  planet  produces  in  a  year 
today.51 

Copernicus: Seven Sentinel  satellites already in  orbit  deliver tens of  terabytes of  data 
every  day.  Six  Copernicus  services  deliver  information  products  from  which  ocean, 
atmosphere  and  climate  models  outputs  are  based  on  HPC  computing:  Copernicus  is 
the biggest provider of Earth observation data in the world.52 

29 

 
 
Genome  sequencing:  As  a single  human  genome  takes  up  100  gigabytes  of  storage 
space, and more and more genomes are sequenced, an estimated 40 exabytes of storage 
capacity will be required for human genomics by 2025.53 

The High-Luminosity CERN Large Hadron Collider (LHC), the successor to the current 
LHC, is planned to come online after 2025. By this time, the total computing capacity 
required  by  the  experiments  is  expected  to  be  50-100  times  greater  than  today,  with 
data storage needs expected to be in the order of exabytes.54 

In  the  more  common  version  of  the  pairing,  “HPC  for  AI”,  AI  uses  an  ecosystem  that 
requires  HPC,  from  embedded  systems,  to  edge  computing  systems  and  large  computer 
centres,  all  interconnected  in  a  secure  fabric  that  exchanges  and  processes  huge  amounts  of 
data.  Autonomously  driving  vehicles  are  a  perfect  example:  embedded  low-power  HPC 
processors will enable real-time decisions in the vehicle, while less urgent decisions will be 
made by interaction with edge computers. More strategic decisions will require complex AI-
powered  models  and  simulations  to  be  run  on  centralised  HPC  systems  that  feed  on  data 
provided by vehicles and edge computers.  

A symmetrical topic of importance is “AI for HPC”. This is less well developed, but the new 
capabilities offered by AI will improve the development and deployment of HPC technologies 
and solutions. In the traditional use of HPC for simulation, model-based approaches are being 
challenged  or  replaced  by  hybrid  modelling  /  AI  techniques  across  many  science  and 
engineering  fields  including  physics,  chemistry,  and  molecular  biology.  For  example, 
machine learning is used to control and drive complex HPC simulations, making them faster, 
more accurate, and self-improving over time. 

3.5 Evolution of supercomputing technologies  

The  trends  in  supercomputing  for  the  next  decade  and  beyond  will  be  driven  by 
disaggregationxxx,  enabled  by  network  improvements,  and  even  greater  specialisation,  as 
necessitated by the end of Moore’s Law. 55 This will be enabled by an open source computing 
platform  (hardware  and  software).  Big  data  and  AI  techniques  are  key  drivers  in  the  global 
race to master the next supercomputing frontier of exascale performance. The next generation 
of supercomputers now under development in the USA and elsewhere is being optimised with 
new  processor  types,  memories,  software  and  system  designs  to  maximise  HPDA  and  AI 
workflows.  An  added  benefit  of  this  trend  is  that  dedicated  HPC  architectures  designed  to 
support such workflows and workloads would reduce the computing time for many tasks and 
would therefore yield a more sustainable energy footprint. 

The whole ICT technology landscape, driven by an exponential increase in big data and 
AI services, displays performance shortcomings and limits similar to traditional HPC-
technologies,  and  ultimately  related  to  the  slowing  of  the  Moore's  law.  As  a 
consequence,  both  big  data  and  HPC  markets  are  shifting  toward  a  new  hardware 
landscape, where specialisation can be used to mitigate technology limits and meet the 
increasing  power  and  performance  needs  of  applications  (HPC  and  non-HPC).  The 
advent of open source software, and by extending the boundaries of open technology to 
all  aspects  of  the  HPC  system  including  hardware,  provides  the  focus,  flexibility  and 

xxx Disaggregation is the separation into components, e.g. separating data-centre equipment, in particular servers, 

into resource components to offer flexibility and ensuring optimal utilization. 

30 

 
 
                                                 
freedom  to  build  new,  specialized  systems  that  can  meet  new  power  and  performance 
requirements….45 

Some of the main trends can be summarised as follows: 

  System  architectures:  Specialisation,  heterogeneity,  modularity  and  composability  will 
be the dominant paradigms at all levels of computer technology, allowing customised and 
cost-effective supercomputing architectures that optimise the use of resources for a class 
of  applications.  The  future  architectures  of  the  exascale  and  post-exascale  era  will  be 
optimised by default to support heterogeneous modelling, simulation and AI tasks.  
“The heterogeneous architecture that underlies El Capitanxxxi is actually uniquely able 
to  host both  artificial  intelligence machine learning  applications, and modelling  and 
simulation….We are already starting to think how to combine them to accelerate our 
ability to simulate beyond the factor of ten that the hardware alone is going to give us 
with El Capitan.” 56 

  Edge/fog  computing:  Further  complexity  arises  with  the  federation  of  computing 
resources  between  HPC  systems  and  the  "edge",  consisting  of  datacentres,  cloud 
computing  services,  local  clusters  and  data  generation  instruments  as  well  as  the  IoT 
devices  (e.g.  sensors,  actors,  local  computing  systems).  On-the-fly  calculations  at 
network-level can reduce the need for expensive data transport.  

  High-speed  intra-networking:  This  is  at  the  core  of  HPC  system  design.  Increasingly 
large systems require optical connections to meet the large distances between the systems 
racks.  Furthermore,  smart  network  technology  such  as  adaptive  routing,  dynamical 
network  reconfiguration,  network  virtualisation,  and  in-network  computations  to  reduce 
data movement and to speed-up collective operations will become of high importance.  

  Reconfigurable  computing:  Being  able  to  orchestrate  the  varieties  of  computing 
resources will enable “reconfigurable computing” at the system level that is able to adapt 
to  the  requirements  of  individual  users.  Along  with  virtualisation  and  containerisation, 
each user can be assigned a “virtual cluster” meeting his/her specific needs.  

  Energy  efficiency.  Moore’s  law  implies  that  energy  and  waste  heat  densities  grow 
exponentially  too.  New  supercomputers  need  more  electricity  and  have  demanding 
requirements, i.e. 5-17 Megawatts (MW) today and up to 50 MW in the near future, and 
switching loads of at least 10 MW on and off in milliseconds. Power management, energy 
efficiency, cooling and recuperation of waste energy are key research fields to reduce the 
operating costs of the systems.  

3.6 New computing paradigms Neuromorphic and Quantum Computing 

New  emerging  computing  paradigms  will  gradually  find  their  way  into  the  traditional 
the  beginning  as  specific  accelerating  processing 
supercomputing 
components for certain applications, and later on as main computing elements. Technologies 
that will progressively find their place in the computing continuum include CMOSxxxii scaling, 
RISC-V,  2.5/3D  stacking,  non-volatile  memory  (NVM),  silicon  photonics,  memristive 

infrastructure, 

in 

xxxi  El  Capitan  is  the  US  National  Nuclear  Security  Administration  (NNSA)  supercomputer  expected  to  reach 
more than 1.5 exaflops, to be installed in Lawrence Livermore National Laboratory (LLNL) in late 2023. 

xxxii CMOS (complementary metal-oxide semiconductor) - semiconductor transistor technology. 

31 

 
 
                                                 
devices,  optical  systems,  analogue  computing,  dataflow  architectures,  “in  memory” 
computing, and more. 

The  effective  use  of  non-traditional  computing  architectures,  like  quantum  computers, 
neuromorphic systems, digital annealers and data flow machines, requires close coupling and 
interaction  with  HPC  machines  that  can  only  be  realised  at  system  level  in  a  modular  and 
composable manner.  

Two novel computing approaches that are starting to show interesting complementarities with 
HPC are neuromorphic and quantum:  

  Neuromorphic computing  

The  development  of  AI,  in  particular  deep  learning,  has  led  to  huge  interest  in 
neuromorphic  architectures,  which  are  inspired  by  a  theoretical  model  of  a  neuron,  or 
“simulated  annealing”  processors.  As  more  and  more  applications  (or  a  part  of  an 
application)  are  mapped  to  this  paradigm,  it  is  worth  developing  specific  circuits  that 
implement only the operations and data paths mandatory for this architecture.  

  Quantum computing 

Quantum  technology  uses  the  properties  of  quantum  effects  –  the  interactions  of 
molecules,  atoms,  and  even  smaller  particles,  known  as  quantum  objects.  Quantum 
computing is  based on quantum bits (qubits), making it possible to  compute millions  of 
possibilities  in  parallel,  instead  of  one  at  a  time  as  classical  computers  do.  Quantum 
computers could  deliver  an impressive processing power for a  given class  of computing 
problems,  namely  those  related  to  prime  number  factoring  or  to  large  optimisation 
problems (representing a combinatorial explosion of computing possibilities). They would 
make  it  possible  to  solve  currently  unsolvable  problems  such  as  the  design  of  new 
materials and drugs, the development of new medicines (conducting virtual drug trials or 
analysing  cancer  cells  to  develop  personalised  treatments),  cryptographic  solutions, 
complex logistics and scheduling problems, risk analysis calculations in finance, etc. 

First  quantum  systems  have  already  been  built  implementing  up  to  53  qubits.  However, 
several  major  technological  advances  will  be  needed  to  build  a  universal  quantum 
computer  of  millions  of  qubits,  which  may  not  exist  for  at  least  one  or  two  decades. 
Europe  is  investing  major  R&D  efforts  in  the  Quantum  Technologies  Flagship  now 
supported under Horizon 2020 and as of 2021 under Horizon Europe. Quantum computing 
projects of the Flagship are developing some of the most advanced physical platforms in 
the world. They are aiming to reach 50 to 100 qubits by mid-2021 and at least 500 qubits 
by  2025,  using  different  quantum  technologies:  trapped  ion  quantum  computers, 
superconducting  quantum  computers,  and  quantum  computer  prototypes  based  on  other 
technologies such as photonics and semiconductors, in combination with built-in quantum 
error-correction  approaches.  They  are  also  developing  quantum  software  and 
programming libraries, and applications addressing industrial use cases and solving other 
concrete problems. 

A  good  overview  of  the  European  roadmap  in  quantum  computing  technologies  is 
provided in the 2020 strategic research agenda of the Quantum Technologies Flagship.57 

The software and applications challenge 

Europe is the world leader in algorithmic and software development in many disciplines. To 

32 

 
 
maintain  this  leadership  and  foster  scientific  breakthroughs,  innovations  will  require 
significant  investments  in  new  algorithms  and  software  optimisation  tools,  in  order  to  fully 
exploit the potential of a modern HPC infrastructure. 

One of the most critical aspects to consider in the exascale era is that most applications will 
require new methods and workflows to exploit the available resources. Some applications will 
continue  to  scale  exceptionally  well,  while  others  are  converging  with  data-driven 
applications and machine-learning-type needs. Composability is the key: new approaches will 
integrate  codes  and  software  components  in  complex  and  scalable  workflows.  New 
programming  environments  and  frameworks  will  enable  the  development  of  composable 
codes  with  portable  performance,  and  a  higher  level  of  abstraction,  reducing  the  costs  of 
integrating  new  paradigms  and  closely  matching  architectural  features  of  increasingly 
diversified and specialised hardware platforms to come. 

A  significant  effort  will  have  to  be  provided  for  new  algorithmic  developments.  Next-
generation computing requires an ambitious programme of algorithm development integrated 
with infrastructure design/development and over longer timescales. It also requires the critical 
system software stack with European components (i.e. a “European Open System Stack”) to 
best  exploit  the  underlying  architecture.  This  European  Open  System  Stack  will  create  an 
open  source  environment  for  both  hardware  and  software  components,  fostering  access  and 
enabling  the  development  of  co-designed  systems.  This  will  also  encourage  additional 
investments  to  generate  new  IPs  in  Europe  (including  licensed  IPs),  for  example,  open 
software  and  repositories  for  scientific  and  industrial  use,  system  tools  and  development 
environments (e.g. debuggers, compilers, performance tools).  

In  the  longer  term,  continued  application  leadership  will  use  novel  computing  approaches 
(e.g.  quantum,  neuromorphic)  for  which  the  necessary  fundamental  mathematical  and 
computer  science  algorithms  are  not  in  place  yet.  Special  attention  should  be  given  to  the 
support of co-design applications where traditional programming environments are extended 
to include new programming and performance tools and libraries for quantum computing. 

3.7 Training and skills for the next decade  
The  Impact  Assessment  of  the  Digital  Europe  programme58,59  identified  several  systemic 
issues in the ICT field, and by extension, in HPC: high demand for ICT workers, difficulties 
in recruiting ICT specialists, insufficient funding for the digital reskilling, etc. Europe needs a 
qualitative and quantitative leap in the education of its workforce in order to make it fit for the 
digital age. There are clear indications that workforce availability and qualifications may be 
the key bottleneck in the industrial and public sectors as well as in the academic system. The 
efforts of PRACE since its start in 2010 have been importantxxxiii but much more needs to be 
done to alleviate the skills deficit. 

Making the vision of European leadership in digital and HPC a reality will rely on attracting 
the  best  talents,  upgrading  competences  and  skills  throughout  the  European  ecosystem,  and 
providing  sufficient  support  to  strengthen  the  knowledge  base  of  HPC  in  Europe,  with  new 
competences,  skills  and  profiles  combining software expertise with  understanding in  industry 

xxxiii PRACE has organised 652 training events gathering more than 16000 participants (76.2% from academia, 
4.6%  from  industry  and  19.2%  from  government,  non-profit  and  supercomputing  centres)  totalling  1861 
training days and nearly 50000 person-training days.  Since 2017 PRACE has developed 4 MOOCs with 8 
on-line deliveries and 15527 participants  

33 

 
 
                                                 
of  frontier  research  in  science  and  innovation.  For  example,  to  take  full  advantage  of  HPC, 
Europe  must  train  more  researchers:  there  is  a  lack  of  computational  scientists  choosing  to 
focus on HPC. We still lack a practical strategy for integrating HPC into the already crowded 
scientific and engineering curricula of European universities. 

Targeted  outreach,  training  and  skill  development  actions,  organised  as  part  of  the  higher 
education system, are needed to attract human resources to HPC and increase the workforce 
skills and engineering knowledge in the European HPC ecosystem. Such actions would need 
to cover, for example, generic and domain-specific HPC knowledge, computational science as 
a career choice, and application and code development.  

An important factor for the success of these measures is the accessibility at local level to skills 
development  actions.  Knowledge and expertise in advanced digital  fields is  not  available in 
all regions in Europe. The combination of activities at both European and national/local level 
should  ensure  that  access  to  development  of  such  expertise  is  made  available  in  every 
Member State and its regions.  

3.8 New political guidelines and Commission priorities for the period 2019-2024 

Actions linked to HPC in the years to come will have to take into account the policy priorities 
highlighted in President von der Leyen’s political guidelines60 for the period 2019-2024:  

  A  Europe  fit  for  the  digital  age  –  achieving  technological  autonomy:  The  HPC 
strategy should contribute to the Union’s digital  autonomy.  It should ensure that Europe 
infrastructures, 
develops  an  autonomous  supply  of  critical  advanced  computing 
technologies,  and  knowledge,  and  it  should  help  provide  the  supercomputing  and  data 
capacities that many key scientific and industrial applications need to fully exploit the data 
revolution,  in  close  combination  with  other  key  digital  technologies,  e.g.  AI,  HPDA, 
cybersecurity and blockchain. 

  An  economy  that  works  for  people  –  Digital  transformation  of  the  economy  and 
European  leadership  in  the  data  economy:  Europe’s  HPC  strategy  should  aim  to 
achieve excellence and maintain European world leadership in key HPC applications for 
European industry (including SMEs), science, and the public sector. It should support the 
next  generation of industrial environments  (e.g.  using big data analytics, AI and  IoT for 
advanced  digital  twins)  and  enable  industrial  HPC  codes,  applications  and  software  to 
exploit  the  performance  of  current  and  future  supercomputers.  The  strategy  should  also 
address the digital divide, ensuring access to the European HPC ecosystem wherever users 
are  located  across  the  EU  and  supporting  Member  States  in  providing  local  support  for 
HPC  competence,  knowledge  and  skills.  This  includes  access  to  supercomputing 
infrastructures,  services  and  solutions  adapted  to  industry’s  needs  (including  SMEs), 
easing and fostering the transition towards a wider uptake of HPC in Europe.  

  A European Green Deal – addressing global challenges: The strategy should contribute 
to  addressing  the  Sustainable  Development  Goals  (SDGs)  and  in  particular  our 
environmental,  climate,  and  other  big  societal  challenges  as  outlined  by 
the 
Communication  on  European  Green  Deal61.  The  Destination  Earth  initiative5  will  bring 
together  European  scientific  and  industrial  expertise  to  develop  a  very  high  precision 
digital  model  of  the  Earth.  This  initiative  will  offer  a  digital  modelling  platform  to 
visualize,  monitor  and  forecast  natural  and  human  activity  on  the  planet  in  support  of 
sustainable development, again supporting Europe’s efforts for a better environment as set 

34 

 
 
out  in  the Green Deal.  As required by Destination Earth, HPC-powered  simulations and 
applications will provide the tools to design efficient solutions transforming the increasing 
number of complex environmental challenges into opportunities for social innovation and 
economic  growth.  The  EuroHPC  JU  is  already  setting  the  pace  worldwide  in  the 
development of low-power technologies for HPC that can be applied in larger sectors of 
the  ICT landscape, helping to  reduce the carbon  footprint of  ICT solutions,  for example 
low-power  processors  and  accelerators.  Greener  computing  should  be  targeted  with 
energy-efficient  supercomputers  and  data  centres,  using  for  example  dynamic  power-
saving and re-use techniques like advanced cooling and recycling of heat produced. 

  A stronger Europe in the world: HPC is a strategic priority for Europe and will be key 
to its national security, defence and technological autonomy. Particularly in combination 
with AI and cybersecurity technologies, HPC will be crucial in helping the Union respond 
to  diverse  and  unpredictable  security  challenges.  For  example,  supercomputers  are 
essential for nuclear simulation and modelling, protection of critical infrastructures, new 
cryptographic  solutions,  and  the  fight  against  terrorism  and  crime  (including  cyber-
criminality and cyber-war). 

In  addition,  the  Commission  presented  in  February  2020  its  ideas  and  actions  for  shaping 
Europe’s digital future62, in which the EuroHPC JU activities can have an important impact: 

  Europe as a trusted digital leader:  The HPC strategy should contribute to the Union’s 
leadership  in  digital  technologies  that  work  for  people,  for  a  fair  and  competitive 
economy, and for a sustainable society, as outlined by the Commission’s communications 
on “A New Industrial Strategy for Europe”63 and “An SME Strategy for a sustainable and 
digital Europe”64. HPC is a key technology contributing to the Union’s strategy to become 
an innovation-driven, value-based and inclusive digital economy and society. 

  Europe  as  a  leader  in  trustworthy  Artificial  Intelligence:  HPC  is  a  critical  tool  to 
building  trust  in  complex  AI-based  solutions,  for  example  with  massive  simulations  to 
evaluate the associated risks and increase transparency and traceability of such solutions, 
or with supercomputer-based support to certification and other features such as respect of 
fundamental rights or non-discrimination. 

  Europe  as  a  leader  in  the  data  economy:  HPC  is  the  “engine”  that  powers  the  data 
revolution, and a key element to fulfil the ambition of putting Europe in the driving seat of 
the global data economy as outlined by the European strategy for data1. Next generation 
HPC infrastructures and technologies are key to support trustworthy and energy efficient 
cloud-based  solutions  and  for  the  exploitation  of  European  public  data  spaces  for  the 
benefit of businesses, researchers and public administrations.  

Finally, the Staff Working Document “Identifying Europe's recovery needs”65 accompanying 
the  Commission  Communication  “Europe's  moment:  Repair  and  Prepare  for  the  Next 
Generation”3  identifies  the  HPC  ecosystem  as  one  of  the  key  digital  value  chains  with 
potential  to  boost  productivity  and  innovation  that  requires  considerable  additional 
investments.  Such  investments  in  the  HPC  ecosystem  will  be  one  of  the  priorities  of  the 
European recovery instruments (“Next Generation EU”) outlined in the Communication “The 
EU budget powering the recovery plan for Europe”.66 

35 

 
 
4.  The Union’s HPC strategic approach for the next MFF (2021-2027) 

4.1 Rationale for a new mission of the EuroHPC JU in the next MFF 

The Union needs to continue its ambitious strategic approach in HPC to support the building 
and  optimal  use  of  the  digital  capacities  that  underpin  economic  prosperity  and  social 
development,  and  bring  the  benefits  of  digital  transformation  to  all  European  citizens  and 
businesses across the Union territory, including in less developed areas. During the past few 
years, political leaders in Europe, but also the USA and China, have recognised the ability of 
leadership-class supercomputers to help transform economies, societies, and understanding of 
the  world.  HPC  has  an  increasing  role  in  advancing  science,  boosting  industrial  innovation, 
and improving people’s daily lives. 

Europe's  scientific  capabilities,  industrial  competitiveness  and  technological  autonomy 
depend  on  unrestricted  access  to  leading  HPC  and  data  technologies  and  full  control  over 
world-class  infrastructures  and  data,  in  order  to  keep  pace  with  the  growing  demands  and 
complexity of the problems to be solved. In particular: 

  Impact on society: HPC is a strategic resource for policy-making. It helps understand an 
ever-changing world and provide policy-makers with the tools to design efficient solutions 
addressing many complex global challenges such as global warming and climate change. 
HPC  is  an  essential  technology  for  transforming  these  challenges  into  innovation 
opportunities  for  growth  and  jobs.  For  example,  HPC  can  be  used  to  find  ways  of 
providing  secure,  clean  and  efficient  energy  (e.g.,  evaluation  of  carbon  reduction 
measures,  simulators  for  fusion  energy,  design  of  performant  photovoltaic  materials  or 
optimising turbines for electricity production); smart, green and integrated urban planning 
(water  and air quality, pollution control,  traffic planning); and  food security, sustainable 
agriculture  and  the  bio-economy  (optimising  the  production  of  food  and  analysing 
sustainability factors such as plagues and diseases control, etc.). 

  Impact on economy: The convergence of HPC with AI, big data, HPDA and the cloud, is 
a  main  innovation  driver  in  the  data  economy.  It  creates  entirely  new  possibilities  to 
extract  useful  and  usable  knowledge  from  the  huge  amount  of  raw  data  produced  every 
day. The computing power of HPC is the “engine” that powers the data economy. HPC is 
an enabler of novel  leading-edge technologies,  applications  and solutions  that open new 
opportunities  for  digitising  European  science,  industry  and  the  public  administrations, 
benefiting all areas of the economy in all regions of Europe. Economic sectors relying on 
HPC  include  manufacturing,  health  and  pharmaceuticals,  automotive,  oil  and  gas, 
aviation, and chemicals: these account for 53.4% of the Union’s GDP, encompassing EUR 
7.56 trillion in value.xxxiv 

  Impact on digital autonomy: Given the impact that digital technologies are having in our 
economy  and society, the EU needs to  ensure its strategic digital  autonomy, in  ensuring 
access to essential supercomputing infrastructures and state-of-the-art HPC technologies. 
The  availability  of  world-class  HPC  resources  and  technological  knowledge  in  Europe 
will encourage researchers and innovators to stay in Europe and ensure that data produced 
by EU research and industry is processed here, instead of moving to regions where high 
data and computing capabilities are available. 

xxxiv See Annex I “Market Analysis and Investments”. 

36 

 
 
                                                 
  Impact on industry’s innovation potential: HPC is today a mainstream technology for 
the  digitisation  of  industry.  The  use  of  HPC,  in  particular  combined  with  AI  and  cloud 
technologies,  is  expanding  to  all  industries  as  current  and  future  broadband  networks 
make it more accessible. HPC has enabled “computationally aware” industrial sectors like 
engineering  and  manufacturing  to  move  up  into  higher  value  products  and  services. 
Moreover, HPC can play a radical transformative role in industry, paving the way to novel 
applications,  for  example,  a  new  generation  of  digital  twins  using  the  powerful,  agile 
computing  capabilities  of  HPC  to  facilitate  new  ways  of  combining  the  virtual  and 
physical worlds. 

  Impact on science: Over the past  half  century, the new domain of scientific computing 
has become the third pillar of modern science, extending and complementing theory and 
experimentation. The applications of HPC in science are countless, and it has become an 
essential  component 
in  nearly  every  field  of  scientific  research.  Many  recent 
breakthroughs  would  not  have  been  possible  without  access  to  the  most  advanced 
supercomputers, for example the Nobel Prizes for Chemistry in 2013 and Physics in 2017.  

  Impact on EU security, defence and national security: HPC is recognised as a national 
strategic  priority  for  the  most  powerful  nations  of  the  world.  Supercomputers  are  in  the 
first  line  for  nuclear  simulation  and  modelling,  cyber-criminality  and  cyber-security,  in 
particular for the protection of critical national infrastructures. Supercomputing is a new 
weapon  in  cyber-war,  and  is  also  increasingly  used  in  the  fight  against  terrorism  and 
crime, e.g., for face recognition or for suspicious behaviour in cluttered public spaces.  

Pursuing a common strategic EU approach in HPC is essential for realising the Union’s 
and its Member States’ ambition to ensure a leading role and technological autonomy in 
the digital economy. The EuroHPC JU will  be a key instrument  for implementing  this 
ambition. 

In Chapter 2, it was shown that the EuroHPC JU has started to deliver its mission after less 
than 18 months of operation. These first achievements confirm the capabilities that the Union 
has when acting and pooling resources together with its Member States.  

The continuation of the EuroHPC in the next MFF (2021-2027) would permit the Union and 
its Member States not only to consolidate but largely amplify these first achievements to the 
benefit of the whole society and economy. However, it would be necessary to adapt the JU’s 
purpose  to  address  the  enormous  challenges  posed  by  the  drivers  for  the  next  10  years,  as 
analysed in Chapter 3. The conclusions of the assessment of the EuroHPC JU of the “Impact 
Assessment  Study  for  Institutionalised  European  Partnerships  under  Horizon  Europe  - 
Candidate  Institutionalised  European  Partnership  in  High-Performance  Computing  (Final 
Report)”30 confirm that an Institutionalised Partnership under Art. 187 TFEU is the preferred 
option for the continuation of the EuroHPC JU, showing higher overall benefits than the other 
options. 

4.2 The mission of the EuroHPC JU in the next MFF 

The mission for the EuroHPC JU for the next  decade would be:  to  develop,  deploy, extend 
and  maintain  in  the  Union  a  world  leading  federated,  secure  and  hyper-connected 
supercomputing, quantum computing, service and data infrastructure ecosystem; support the 
production  of  innovative  and  competitive  supercomputing  systems  based  on  a  supply  chain 
that will ensure components, technologies and knowledge limiting the risk of disruptions and 

37 

 
 
the development of a wide range of applications optimised for these systems; widen the use of 
this supercomputing infrastructure to a large number of public and private users, and support 
the development of key skills for European science and industry. 

EuroHPC JU would realise this ambitious mission, ensuring that the Union enjoys world-class 
supercomputing and data capabilities according to its economic potential, matching the needs 
of  European  users,  and  with  the  required  technological  autonomy  in  critical  HPC 
technologies.  

The EuroHPC JU  should put in place an all-encompassing approach that ensures commitment 
and  support  of  national  and  EU  investments,  with  the  critical  participation  of  the  Union, 
Member States, Private Members, and collaboration with other key European players such as 
PRACE and GEANT. 

A revised Council Regulation for the continuation of the EuroHPC JU will need to be adopted 
during 2020 to implement the above vision and mission by using the financial support from 
relevant programmes of the next MFF without interrupting the EuroHPC JU’s activities. This 
Regulation should also incorporate the lessons learnt since the establishment of the EuroHPC 
JU (e.g., governance, administration, etc.) as mentioned in section 2.4 of this document.  
In the revised Regulation, which covers the period 2021-2033xxxv, the EuroHPC JU will need 
a clear mandate to address the following objectives involved in its overall mission:    

Infrastructure Investment:  

To  invest  in  a  secure,  demand-oriented  and  user-driven  world  class  supercomputing, 
including quantum computing, service and data infrastructure (composed of the best existing 
computing and networking technologies, and if possible European) for seamlessly providing 
advanced computing and data services to public and private users in Europe. 

The  first  objective  of  the  EuroHPC  JU  would  be  to  support  investments  on  advanced  and 
highly interconnected supercomputing capabilities all over Europe, from petascale to exascale 
and  post-exascale,  and  integrating  novel  capabilities  including  neuromorphic  and  quantum 
computing  approaches.  In particular, the EuroHPC JU would carry out  ambitious actions to 
integrate quantum technologies in HPC infrastructures.  By doing so, the JU will be able to 
meet the needs of European users and their applications, and to encourage a thriving scientific 
and industrial innovation ecosystem in Europe.  

This objective has a particular focus on: 

–  The  acquisition  and  deployment  of  a  leading-class  supercomputing  and  data 

infrastructure; 

–  The  integration  of  novel  computing  approaches  and  technology  capacities  as  they 
become available in hybrid infrastructures, e.g. quantum computing infrastructures;  

–  The  hyper-connectivity  of 

infrastructure  with  state-of-the-art  networking 
technologies  to  securely  interconnect  all  EuroHPC  supercomputers  and  make  them 
widely accessible across Europe. 

the 

xxxv  This  period  covers  the  next  MFF  (2021-2027),  the  period  required  for  depreciating  the  operation  of  any 
supercomputer(s)  that  the  JU  may  acquire  at  the  very  end  of  the  MFF  -  typically  5  years  -  and  the  period 
required for winding up the JU. 

38 

 
 
                                                 
Federating  the  supercomputing  and  data  infrastructure,  interconnecting  it  with  the 
European common data spaces, and providing EU-wide services to a wide range of users  

The second objective is related to the federation of the supercomputing and data infrastructure 
and its secure interconnection with  the European  common data spaces and cloud  ecosystem 
for seamlessly providing advanced computing and data services to public and private users in 
Europe. 

This objective will have a particular focus on: 

– 

– 

federating the hyper-connected national and European HPC, quantum service and data 
resources into a common platform, able to offer resources, tools and access services at 
European  level  (for  example,  cloud-based  HPC,  HPDA  tools,  interactive/real-time 
services, etc.); 

Interconnecting the federated supercomputing, quantum service and data infrastructure 
with  the  European  public  data  spaces  and  cloud  ecosystem  for  seamless  service 
provisioning to a wide range of public and private users in Europe.  

Technology Ecosystem development:  

To  further  develop  and  maintain  a  competitive  ecosystem  in  Europe  contributing  to  the 
technological autonomy of the Union in the digital economy, by supporting the development 
of advanced future computing technologies and architectures and their integration on leading 
supercomputing systems and by supporting advanced applications optimised for such systems. 

The  third  objective  of  the  EuroHPC  JU  would  be  to  support  R&I  activities  in  (i)  next 
generation  low-power  supercomputing  technologies,  innovative  software  and  advanced 
supercomputing  systems  for  exascale  and  post-exascale  computing  that  integrate  these 
technologies  as  well  as  other  emerging  supercomputing  platforms  (neuromorphic  or 
quantum);  and  (ii)  innovative  applications  for  public  and  private  users  that  exploit  the 
capabilities of the new supercomputing systems  while addressing in  particular the emerging 
convergence of HPC with AI, HPDA and cloud technologies. 

By  doing  so,  the  JU  will  allow  a  European  supply  chain  that  ensures  the  development  of 
components, technologies and knowledge limiting the risk of disruptions in a wide range of 
key  technology  and  application  areas  that  reach  beyond  HPC  and,  in  the  long  run,  feed 
broader ICT markets with EU-made technologies. It will also to support the HPC science and 
user  industry  to  undergo  a  digital  transformation  and  boost  its  leadership  and  innovation 
potential.  

This objective has a particular focus on: 

–  The development and integration of technology elements in the full value chain, from 
the  processor  components,  basic  software  and  tools,  programming  environments  etc. 
all the way to critical applications for science and industry; 

–  Ensuring 

technological  autonomy 

in  critical 

technologies, 

infrastructures  and 

applications (including e.g. cybersecurity and defence applications); 

–  Fostering a low-energy consumption approach to the development of HPC technology 

and supercomputing systems; 

–  Ensuring  European  R&I  activities  are  linked  with  the  development,  acquisition  and 
deployment  of  leading-class  supercomputers  and  other  infrastructure  based  on 

39 

 
 
European  technology  and  components.  This  is  related  to  the  strong  need  to  create  a 
chain  that  runs  from  R&I  to  the  delivery  and  operation  of  world-class  HPC  systems 
co-designed by users and suppliers in Europe; 

–  Using  specific  innovation  procurement  or  targeted  actions  that  combine  financial 
support of the necessary non-recurring engineering costs (R&I) with the acquisition of 
the resulting operational supercomputers; 

–  Keeping  in  the  EU  the  intellectual  property  (IP)  generated  by  EuroHPC-funded 
activities, and supporting the commercialisation and exploitation of this IP to benefit 
the  Union  (subject  to  conformance  with  the  relevant  IP  framework  of  the 
corresponding funding programme); 

–  Fostering  the  development  and  use  of  scientific,  industrial  and  public  sector 
applications in key domains for Europe, in particular combining HPC with other key 
technologies such as AI, HPDA and cloud. 

Widening  HPC  use  and  the  development  of  key  HPC  skills  that  European  science  and 
industry need. 

The  fourth  objective  of  the  EuroHPC  JU  would  be  to  (i)  ensure  that  its  HPC  and  data 
infrastructures are optimally adapted to the different needs of scientific and industrial users, in 
order  to  ensure  the  wide  uptake  of  HPC  and  make  a  major  contribution  to  the  digital 
transformation of Europe; and (ii) invest in providing Europe with a knowledgeable leading 
scientific community and the competences and skills critical for scientific leadership and for 
the digital transformation of industry. 

This objective has a particular focus on: 

–  Fostering the industrial access and use of HPC and data infrastructures for industrial 
innovation,  adapted  to  industrial  needs  (including  SMEs),  exploiting  the  current  and 
future HPC and data infrastructures, and easing the transition towards the wider uptake 
of HPC; 

–  Developing the necessary skills for the digital transformation of science and industry, 
taking into account synergies with other programmes and instruments, in particular the 
Digital Europe programme.58  

5.   The main activities of EuroHPC JU in the next MFF 

5.1 The new pillars of activity  

The wide range and complexity of the future objectives of the EuroHPC JU require a high-
level  structure  to  guide  understanding  and  implementation  of  the  JU’s  current  and  future 
activities. In particular, this structure would be a means of matching activities and objectives 
with the planned funding programmes of the next MFF in the form of five pillars of activity: 
HPC  Infrastructure,  HPC  Federation  and  Services,  HPC  Technologies,  HPC  Applications, 
and Leadership in HPC use and skills development: 

40 

 
 
 
 
 
Figure 7 - EuroHPC: Pillars of Activity 

1.  Infrastructure  

The objective of this pillar would be the acquisition and deployment in the Union of a world-
class  secure  supercomputing,  quantum  computing,  service  and  data  infrastructure  composed 
of  the  best  existing  supercomputing,  quantum  computing  and  data  technologies  and  hyper-
connected with  state-of-the-art  communication (reaching terabitsxxxvi in  the backbone). Parts 
of this infrastructure could be specifically dedicated for industrial use. 

The  infrastructure  will  progressively  integrate  the  most  advanced  computing  generation 
systems:  petascale,  pre-exascale,  exascale  and  post-exascale,  as  well  as  neuromorphic 
technologies, quantum simulators, and quantum computers.  

In quantum computing, the EuroHPC JU would invest in at least two generations of state-of-
the-art  pilot  quantum  computers  and  quantum  simulators  and  their  integration  in  the  JU’s 
HPC infrastructures. These pilot systems would be based on European technologies that are 
mainly funded under the Quantum Technologies Flagship (under Horizon 2020 and Horizon 
Europe).  They  would  have  a  proven  capability  to  be  operated  and  integrated  in 
supercomputing environments. They would be used either as stand-alone operational systems 
or  as  computing  accelerators  to  form  “hybrid”  machines,  i.e.  machines  interconnected  with 
the  EuroHPC  JU’s  supercomputers  and  blending  quantum  and  classical  approaches.  Both 
types and their software and programming tools would be openly available via the cloud, for 
users to experiment and to develop future application libraries. 

The following table provides the tentative roadmap for the development and deployment of a 
world-class EuroHPC JU supercomputing and quantum computing infrastructure: 

2021 

2022 

2023 

2024 

2025 

2026 

2027 

HPC 
systems 

Several pre-exascale systems and  
2 exascale HPC systems 

One or more exascale and 
post-exascale HPC systems 

Quantum 
Systems 

First generation of 
quantum computers 
(stand-alone systems or 
in hybrid systems as 
accelerators of HPC ) 

Fully programmable 
quantum simulators 
interfacing with 
HPC systems 

Second generation of 
quantum computers (stand-
alone systems and hybrid 
systems integrated in HPC) 

xxxvi A communication network capable to transfer data at 1 trillion (1012) bits per second. 

41 

 
 
  
 
 
 
 
                                                 
The main activities of the infrastructure pillar are the following: 

  2021-2024: Acquire and deploy two top leading-class exascale supercomputers owned by 
the EuroHPC JU that could be built for example with technology based on the efforts of 
the EPI Consortium. These supercomputers will be owned by the EuroHPC JU; 

  2022-2024: Acquire and deploy mid-range supercomputers complementing the top-ranked 
systems above. These supercomputers will be co-owned by the EuroHPC JU and Member 
States; 

  2021-2025: Develop and deploy hybrid supercomputing infrastructures, by integrating in 
the  HPC  infrastructure  the  most  advanced  quantum  simulators  and/or  future  quantum 
computing platforms, as follows: 

–   2021-2022: start equipping major computing centres with the best available European 
quantum computers, some interconnected with high-end HPC machines as accelerators 
for specific applications, accessible via the cloud; 

–   2023-2024:  procure  fully  programmable  quantum  simulators  reaching  at  least  1000 

individual quantum units (atoms/ions); 

–   2025-2026: build and deploy the second generation of quantum computers (based on 
processors  of  at  least  200  high  fidelity  qubits)  as  stand-alone  systems  or  hybridised 
with high-end HPC machines and accessible via the cloud. 

  2026-2027: Acquire top leading-class post-exascale EuroHPC supercomputers owned by 

the EuroHPC. These supercomputers will be owned by the EuroHPC JU; 

  Support  the  acquisition  and  deployment  of  a  secure  supercomputing  and  data 

infrastructure for industrial users;  

  Guarantee  hyper-connectivity  of 

infrastructure  by  securely 
interconnecting all European supercomputing centres and make them widely accessible to 
public and private users across Europe; 

the  above  EuroHPC 

2.  Federation and Services  

The  objective  of  this  pillar  would  be  to  provide  EU-wide  access  to  computing  and  data 
resources and services throughout Europe for the research and scientific community, industry 
(including  SMEs)  and  the  public  sector.  This  pillar  will  address  the  federation  of  EU  and 
national supercomputing resources and the provision of secure cloud-based services to a wide 
range of application with different access and security needs, including services based on the 
use of European common data spaces. 

The main activities of the infrastructure pillar are the following: 

  Federating national and European HPC and data resources into a common platform, able 
to securely offer HPC resources, tools and access services at European level (for example, 
cloud-based HPC, HPDA tools, real-time simulations, etc.) for a wide range of public and 
private users.  

  Developing  and  adapting  the  supercomputing  and  data  infrastructure  in  highly  flexible 
configurations tailored to a wide range of application and computing needs of users from 
academia,  industry  and  the  public  sector,  including  for  European  Open  Science  Cloud 

42 

 
 
 
users.  This  will  also  address  the  development  of  interfaces  to  other  public  and  private 
cloud providers to offer HPC-based services with different security requirements.  

  Developing  specific  access  and  HPC-based  services  based  on  European  common  data 
spaces  in  areas  of  public  interest  across  the  Member  States  addressing  essential  societal 
challenges such as e.g. transport and climate change. 

 

Interconnecting  securely  the  federated  supercomputing  and  data  infrastructure  with  the 
cloud  ecosystem  for  interoperability  and  service  provisioning  to  a  wide  range  of  public 
and private users in Europe.  

3.  Technologies 

The  activities  in  the  technologies  pillar  would  be  organised  with  the  aim  to  ensure  the 
development of a source of innovative HPC technology (hardware and software) in Europe.  

A major objective of the pillar will be to support an ambitious research and innovation agenda 
for developing a competitive and innovative supercomputing ecosystem addressing hardware 
and  software  technologies,  and  their  integration  into  computing  systems.  Focus  will  be  on 
energy-efficient HPC technologies that will cover the HPC sector and also broader technology 
sectors  (e.g.  extreme-scale,  high-performance  big-data  and  emerging  applications  based  on 
edge computing). 

Another major objective of the pillar will be to develop the technologies and systems required 
for  the  interconnection  and  operation  of  classical  supercomputing  systems  with  other,  often 
complementary computing technologies, in particular neuromorphic or quantum computing. 

The  pillar  will  cover  the  entire  scientific  and  industrial  value  chain,  from  research  to 
prototyping, piloting and demonstration.  

Examples of activities that this pillar will support include: 

  Energy-efficient  exascale  and  post-exascale  computing  architectures,  technologies 

and systems and their integration in pilot systems. This includes: 

–  Development  of  the  next  generation  of  technology  building  blocks  for  high-end 
computing, 
technologies  (low-power  processors  and 
accelerators,  interconnects,  etc.),  and  the  software  stack  (programming  models  and 
environments, compilers, optimisation tools, operating systems, etc.).  

including  both  hardware 

–  The  establishment  of  specialization,  heterogeneity,  modularity  and  composability  as 
the dominant paradigms at all levels of computer technology to allow for customised 
and cost-effective supercomputing architectures that optimise the use of resources for 
a class of applications. 

– 

Integration  of  technology  building  blocks  into  novel  HPC  architectures  for  exascale 
and post-exascale systems, from the first level of basic elements to system integration 
in  prototypes  and  pilots  (up  to  pre-operational  environments).  This  includes  support 
for R&I in hardware and software required for building top-class exascale machines as 
well as on novel cooling technologies. 

  Novel  algorithms  and  software  codes  and  tools    for  advanced  supercomputing 

systems 

43 

 
 
–  Developing a novel generation of mathematical methods and algorithms for European 
leadership in digital twin technologies, notably those relying on modelling, simulation 
and optimization methods enriched by data analytics and intensive computing; 

–  Codes  and  software  components  following  the  composability  approach  integrated  in 
complex  and  scalable  workflows,  including  the  development  of  a  European  Open 
Software.  Productive  programming  environments  and  frameworks  enabling  the 
development  of  composable  codes  with  portable  performance,  and  a  higher  level  of 
abstraction, reducing the costs of integrating new paradigms and closely matching the 
architectural  features  of  increasingly  diversified  and  specialised  future  hardware 
platforms, in particular based on open hardware and software.  

  Hybrid  computing  pilots,  covering  the  developments  needed  to  build  pilot  quantum 
computing and simulation platforms and to interconnect them with the HPC infrastructure 
and the developments  needed to  interconnect  HPC with  other computing platforms (e.g. 
neuromorphic or other) and ensure their effective operation. 

A  co-design  approach  is  necessary  in  technology  development  (in  particular  in  the 
prototyping and piloting phases) between suppliers and users, defining new architectures and 
better computational methods and algorithms that are adapted to real  application needs. Co-
design ensures that hardware and software architectures fit the needs of key relevant/mission 
critical applications by applying the necessary technical trade-offs in system design. The pilot 
and  prototypes  demonstrating  the  viability  of  technologies  for  exascale  performance  will 
serve as ‘stepping stones’ towards future fully operational exascale systems. These prototypes 
would be installed in supercomputing centres for wide user testing and validation. 

4.  Applications  

This  pillar  would  aim  to  achieve  excellence  and  maintain  European  leadership  in  HPC 
applications that are key for European science, industry and the public sector. Scientific and 
industrial HPC codes, applications and software packages in key areas for Europe will be co-
designed,  developed,  ported  and  optimised  to  fully  exploit  the  performance  of  current  and 
future computing systems. Examples of activities in this pillar include: 

  Support  to  HPC-powered  codes,  applications  and  tools  in  all  phases  (such  as  in  co-
design,  development,  porting,  re-structuring,  optimisation,  up-scaling,  re-engineering, 
etc.) in critical domains for extreme scale computing and data performance. This support 
could be implemented through a variety of actions, e.g.: 
–  For scientific users: promoting Centres of Excellence in HPC applications (CoEs)xxxvii, 
in  areas  where  user  communities,  in  collaboration  with  other  HPC  stakeholders,  can 
develop  or  scale  up  existing  parallel  codes  and  applications  to  fully  exploit  future 
exascale and extreme performance computing capabilities. 

–  For  industry:  large  initiatives  on  industrialisation  and  deployment  of  HPC  software 
and codes, ensuring that professional industrial software codes and services (including 
e.g.  compilers,  tools,  standards,  etc.)  can  be  adapted  to  make  full  use  of  new  HPC 
performance  capabilities.  This  includes  the  development  of  tools  for  modelling  and 

xxxvii CoEs are user-driven focal points for application excellence in key scientific or industrial areas, and for co-
design with the European technology development to ensure that European technologies and systems fit the 
needs of applications and their users. 

44 

 
 
                                                 
simulation of complex industrial systems (such as systems of systems), for example to 
simulate digital twins. 

  Development of large-scale industrial pilot test-beds and platforms for HPC applications 
and  services,  including  HPDA  and  AI-focused  ones,  addressing  the  feasibility,  scaling, 
and demonstration of secure HPC environments in key industrial sectors. 

5.  Leadership in HPC use and skills development  

This pillar would aim to widen the scientific and industrial use of HPC applications, and to 
provide Europe with a knowledgeable leading scientific community and skilled workforce. Its 
activities should help the digital transformation of industry and strengthen the knowledge base 
of  HPC  in  Europe  with  new  competences  and  skills.  Examples  of  activities  that  this  pillar 
could support include: 

  Further  supporting  the  development  and  coordination  of  national  HPC  Competence 
Centres,  and  encouraging  and  supporting  exchange  of  best  practices,  the  sharing  of 
existing libraries of HPC codes and access to upgraded HPC application codes. 

  Facilitating  the  access  to  the  best  HPC  and  data  intensive  codes  and  tools  in  the  most 
innovative  scientific  and  industrial  applications  available  now  and  in  the  future  across 
Europe,  notably  through  Centres  of  Excellence  and  Competence  Centres.  This  includes 
federating  capabilities,  exploiting  available  competences,  and  ensuring  that  application 
knowledge and expertise has the widest geographical coverage in the Union.  

  Deployment  of  industrial-oriented  HPC  infrastructure  and  associated  tools,  software 
environments and service platforms for industrial innovation. In particular, this addresses 
the  fair  access  to  HPC  infrastructures  adapted  to  the  needs  of  different  industrial  users, 
from  large  industry  users  to  SMEs,  e.g.  in  terms  of  flexibility,  ease  of  use,  on-demand 
capacity, trust, security and safety, confidentiality, security, dedicated storage, etc.  

  Specific actions for SMEs, enabling European SMEs to benefit from the use of computing 
and  simulation  services  in  a  fair  and  transparent  way,  e.g.  similar  to  the  current 
Fortissimo37 experiments.  

  Supporting  the  development  of  digital  skills,  training  and  education,  attracting  human 
resources to HPC and increasing Europe’s workforce skills and engineering knowledge: 

–  Empowering  people  working  in  HPC  and  its  convergence  with  advanced  digital 
technologies  such  as  data  analytics,  AI,  blockchain,  cybersecurity,  etc.  Such  actions 
could include for example: Master’s programmes in HPC and computational science; 
short-term  HPC  training  courses;  job  placements/traineeships  involving  the  use  of 
HPC  in  real  environments;  HPC  hackathons,  hands-on  schools  and  training  through 
research in advanced laboratories, etc. 

–  Industry-specific  training,  for  example  combined  with  consultancy  and  trial  use  of 
HPC  infrastructures  through  national  points.  For  end-user  SMEs,  this  could  include 
hands  on  training  and  solving  real  use  cases,  and  SME-tailored  courses  and  support 
offerings like staff exchange programmes with research and academia. 

  Other awareness-raising and dissemination actions not specifically addressed above. 

45 

 
 
5.2 The supporting programmes of the next MFF 
The Digital Europe Programme58, Horizon Europe67 and Connecting Europe Facility-268 are 
the main funding programmes in the next MFF (2021-2027) that could be used to finance the 
EuroHPC  pillars  of  activity  described  above.  The  Commission’s  proposals  for  these 
programmes include provisions for supporting the JU’s activities. 

  The Digital Europe programme (DEP) is the first EU programme specifically designed 
to  support  the  digital  transformation  of  the  European  economy  and  society  through 
capacity and capability building. The Commission proposed a budget of  EUR 9.2 billion 
for DEP to align the next long-term EU budget with increasing digital challenges.  

HPC is the biggest DEP priority area with a proposed EUR 2.7 billion budget. Additional 
funding  for  HPC  is  also  foreseen  in  the  “Digital  Skills”  priority  area,  which  has  a  total 
budget of EUR 700 million. The EuroHPC JU will use DEP support for capacity building 
activities, i.e. the activities described in  the EuroHPC pillars on “Infrastructure” i.e., the 
acquisition  of  both  HPC  and  pilot  quantum  computing  infrastructure,  “Federation  and 
Services”,  and  “Leadership  in  HPC  use  and  skills”.  In  addition,  the  DEP  could  also 
support some of the activities in the “Applications” pillar. 

  Horizon Europe (H-E) is the new research and innovation (R&I) framework programme 
for  the  period  2021-2027,  succeeding  Horizon  2020.11  The  common  understanding 
reached  with  the  Council  on  the  Commission’s  H-E  proposal  foresees  support  to  HPC 
related  R&I  activities  under 
Industrial 
Competitiveness', cluster IV “Digital, Industry and Space”.  

'Global  Challenges  and 

its  Pillar 

II 

H-E would support the R&I activities included in the EuroHPC JU’s “Technologies”, and 
“Applications”  pillars.  While  there  is  no  H-E-specific  budget  pre-allocated  for  HPC-
related activities (the budget to be allocated to the European Partnerships portfolio under 
H-E is  still to  be defined), it is  expected that the contribution  from  H-E would fund the 
JU’s R&I activities. These activities do not include R&I support  in quantum computing, 
which are to be funded under the Quantum Technologies Flagship. 

  Connecting Europe Facility-2 (CEF-2) is the successor to the previous CEF programme 
to promote growth, jobs and competitiveness through targeted infrastructure investment at 
European  level.  The  EuroHPC  JU  will  use  CEF-2  funds  to  support  a  leading-class 
communication backbone for interconnecting the supercomputing and data infrastructures 
and  the  European  common  data  spaces  of  the  “Infrastructure”  and  the  “Federation  and 
Services” pillars of EuroHPC. 

The following table summarises how the three above funding programmes could be used to 
implement the four overall objectives of the EuroHPC JU presented in Section 4.2 above. 

EuroHPC Objectives 

DEP 

H-E 

CEF-2 

Infrastructure Investment 

√ 
(acquisition of 
computing 
systems) 

Federation of the JU’s 
Infrastructure and connection 
with data spaces 

√ 

46 

√ 
(networking of 
the JU’s 
infrastructures) 

 
 
 
 
 
 
Ecosystem development 

√ 
Support to HPC-
powered codes, 
applications and 
tools for industry 

√ 
(R&I activities for 
HPC technologies 
and innovative 
applications) 

Widening HPC use and the 
development of key HPC 
skills 

√ 

5.3 Interactions and synergies with other strategic objectives and policies   

The  EuroHPC  JU  should  develop  synergies  and  cooperation  activities  with  other  digital 
strategic  priorities  and  technologies  included  in  the  next  MFF  programmes.  Examples 
include: 

Synergies in DEP: The JU should ensure synergy of its activities with the other DEP priority 
areas, namely artificial intelligence, cybersecurity, advanced digital skills, and ensuring wide 
use of digital technologies across the economy and society. 
  Artificial Intelligence: As explained in Section 3.3xxxviii, the convergence of HPC and AI 
is a critical technology and market driver for applications that rely on big data and HPDA. 
In  particular,  EuroHPC  can  play  a  key  role  in  the  Union’s  plans  to  promote  support 
centres  for  data  sharing  in  the  European  data  spacexxxix  that  could  accelerate  the 
development and uptake of AI in different application sectors. This is especially so as the 
JU’s  new  supercomputers  are  designed  to  fit  the  needs  of  AI  applications.  This  calls  in 
turn  for  increased  co-design  and  balanced 
investments  between  AI  algorithms, 
applications and next-generation supercomputers. 

  Cybersecurity:  HPC  is  essential  for  the  state-of-the-art  cybersecurity  equipment  and 
infrastructure that the DEP will support. The HPC computing power unlocks the power of 
security software and tools, usually in combination with AI-based approaches.xl There is a 
tangible need for supercomputing power in cybersecurity, as HPC minimises the impact of 
the time taken for massive checks and enables advanced solutions to prevent, identify and 
anticipate defensive measures against cybercrime and cyberattacks. 

  Advanced digital skills: The EuroHPC JU will seek synergies with the DEP priority area 
of  digital  skills.  The  JU  is  already  supporting  HPC  skills  development  for  science  and 
engineering, e.g. through PRACE 69 and the HPC Centres of Excellence. In the future, the 
HPC  Competence  Centres  will  coordinate  their  HPC  training  and  skills  developments 
activities with the local ones in the JU’s Participating States. 

  Ensuring  the  wide  use  of  digital  technologies  across  the  economy  and  society:  The 
EuroHPC  JU  is  an  example  of  the  deployment  of  state  of-the-art  digital  technologies, 
infrastructures and services for a wide range of users. The JU will thus establish synergies 
with this priority area, and in particular with the Digital Innovation Hubs supporting the 
digitalization process of  SMEs. For  example, For example, such hubs can act locally  as 

xxxviii See section 3.3 and Annex II of this document for further details on the HPC-AI convergence  
xxxix See COM(2018) 232 final and COM(2018) 237 final of 25.04.2018. 
xl See Annex II of this document for examples on the use of HPC/AI in cybersecurity. 

47 

 
 
 
 
 
 
                                                 
antennas for national HPC Competence Centres or even offer dedicated HPC services in 
synergy with Fortissimo37, the PRACE SHAPE44 programme, the SESAMENet70, etc. 

Synergies  in  Horizon  Europe  (H-E):  The  EuroHPC  JU  should  focus  on  R&I  activities  for 
high-end computing technologies. The JU would develop synergies with other H-E areas and 
partnerships that will support R&I activities complementary to the EuroHPC JU’s. Examples 
include: 
  Activities  of  the  successor  of  the  ECSEL  Joint  Undertaking71,  or  of  the  Quantum 
Technologies  Flagship  which  would  support  advanced  computing  technologies  not 
specifically  oriented  towards  high-end  HPC,  such  as  low-power  processors  for  AI  or 
automotive, or based on quantum-computing components, etc. 

  Big  data  technologies,  methodologies  and  tools  for  privacy-preserving,  data 

interoperability and data provenance tracking, etc. 

  The European Open Science Cloud (EOSC)72: Some of the computing capacities of the 
EuroHPC  systems  could  be  offered  to  the  EOSC  research  communities  for  supporting 
their supercomputing needs. This will be done by aligning the JU’s accessibility structures 
through the user interface of the EOSC portal. 73 

Synergies with other programmes and initiatives: The EuroHPC JU should be developing an 
open  public  infrastructure  accessible  to  any  public  and  private  user.  It  will  thereby  remain 
open  to  many  other  European  and  national  programmes  and  initiatives  focusing  on  climate 
change,  health  data  analysis,  and  crisis  and  emergency  management  situations.  The  JU  will 
strive to forge links and synergies with all these related programmes and their stakeholders. In 
particular,  the  EuroHPC  JU  will  contribute  to  the  initiatives  steaming  from  the  European 
Strategy for Data1 with the provision of services for users  exploiting the European common 
data spaces.  

5.4 International Cooperation  
As  recommended  in  the  Vision  paper  of  the  EuroHPC  JU  Industrial  Advisory  Board45, 
EuroHPC  should  promote  and  raise  the  level  of  international  collaboration  to  solve  global 
scientific  and  societal  challenges,  while  promoting  competitiveness  of  the  European  HPC 
supply and user ecosystem. International collaboration activities of benefit to the Union could 
be established in the following areas of activity:  

  Access  to the JU’s  supercomputing  and data infrastructure:  The EuroHPC JU could 
establish arrangements based on clearly defined rules for providing dedicated access to its 
infrastructures  to  users  from  other  regions  of  the  world.  Such  access  is  crucial  for 
attracting  and  keeping  talent,  promoting  innovation  and  exchanging  knowledge  for 
science  and  industry  in  Europe.  Access  should  be  guided  where  this  collaboration  is  of 
clear interest for the European Union. 

  Applications: Most of the grand challenge applications that are going to run on exascale 
platforms  are  developed  through  international  scientific  collaborations  where  European 
scientists  play  a  key  role,  contributing  to  developer’s  environment  tools  and  system 
software.  The  EuroHPC  JU  can  foster  international  collaboration  in  such  applications 
addressing  global  challenges,  with  the  overall  aim  of  achieving  European  leadership  in 
application and use of HPC. 

48 

 
 
  Technology  supply:  International  collaboration  can  help  the  Union  address  the  current 
dependence  of  the  European  HPC  industry  on  non-European  sources  for  critical 
technology  and  especially  hardware  components.  For  example,  the  EuroHPC  JU  could 
focus  international  cooperation  on  projects  that  enable  European  industry  fill  in  the 
technology and knowledge gaps in the value chain and/or help negotiate partnerships that 
include  IP  sharing  with  financial  return  for  European  industry  on  the  world  market.  For 
promoting  the  latter,  the  EuroHPC  JU  could  encourage  the  collaboration  of  global  IT 
vendors with European partners for example through the establishment of joint ventures or 
the creation of joint labs or other initiatives that respect the EU model of IP sharing and 
financial return. 

Given the size of the investment that will be required, international collaboration would be 
extremely beneficial for post-exascale systems development as well as the deployment of 
heterogeneous supercomputer networks at a global scale. 

49 

 
 
 
Acronyms and abbreviations 

AC 

AI 

ASCR  

BDVA 

CAGR 

CEF 

CoE 

cPPP 

DEP 

DL 

DSM 

EC 

EIB 

EPI 

ERIC 

Associated Country to the Horizon 2020 Programme 

Artificial Intelligence 

Advanced Scientific Computing Research 

Big Data Value Association 

Compound annual growth rate (CAGR) 

Connecting Europe Facility 

Centre of Excellence 

Contractual Public-Private Partnership 

Digital Europe Programme 

  Deep Learning 

Digital Single Market 

European Commission 

European Investment Bank 

  European Processor Initiative 

European Research Infrastructure Committee 

ETP4HPC 

European Technology Platform for High-Performance Computing 

EU 

Exascale 

European Union 
Computing systems capable of 1018 Floating Point Operations per Second  

FET 

Flop 

FP7 

FPA 

GDP 

H2020 

HE 

HPC 

Future and Emerging Technologies 

Floating Point Operations per Second 
7th EU Framework Programme for Research & Innovation 

Framework Partnership Agreement 

Gross Domestic Product 

Horizon 2020 Framework Programme for Research & Innovation 

Horizon Europe Framework Programme for Research & Innovation 

High-Performance Computing  

HPDA   

  High Performance Data Analytics 

ICT 

INFRAG 

IP/IPRs 

ISV  

JU 

MFF 

Information and Communication Technology 

Infrastructure Advisory Group of the EuroHPC JU 

Intellectual Property / Intellectual Property Rights 

Independent Software Vendors 

Joint Undertaking (as defined by Article 187 Treaty of the Union) 

Multi-annual Financial Framework 

50 

 
 
 
 
ML 

MOOC 

MS 

NSA 

PPP 

Machine Learning 

Massive Open On-line Courses  

Member State of the European Union 

(US) National Security Agency 

Public-Private Partnership 

PRACE 

Partnership for Advanced Computing in Europe 

Pre-exascale 

Computing power near the exascale performance (i.e. 0.1-0.6 exascale) 

R&D / R&I 

Research and Development / Research and Innovation 

RIAG 

ROI 

SME 

SRA 

WP 

Research and Innovation Advisory Group of the EuroHPC Joint Undertaking 

Returns on Investment 

Small- and Medium-sized Enterprise 

Strategic Research Agenda 

Work Programme 

51 

 
 
List of Figures 
Figure 1 - Map of the EuroHPC JU Participating Countries .................................................... 9 

Figure 2 - World top 500 supercomputers - regional share .................................................... 14 

Figure 3 - Share of HPC systems in global top-10 per country ............................................... 14 

Figure 4 - Computing power of world top 10 supercomputers ................................................ 14 

Figure 5 - Members of Consortia in EuroHPC JU supercomputers ....................................... 15 

Figure 6 - European computing power in 2020 (forecast) ...................................................... 16 

Figure 7 - EuroHPC: Pillars of Activity .................................................................................. 41 

Figure 8 - Return on investments (ROI) of HPC ...................................................................... 53 

Figure 9 - Secondary Impact of HPC on the US Economy ...................................................... 54 

Figure 10 - HPC Server market by region ............................................................................... 55 

Figure 11 - The Worldwide HPC server market ...................................................................... 56 

Figure 12 – Global HPC Market by vendor shares ................................................................. 56 

Figure 13 - Vendors of systems installed in the EU ................................................................. 58 

Figure 14 – HPC in the Cloud market ..................................................................................... 60 

Figure 15 - Projected Exascale Systems dates ......................................................................... 62 

Figure 16 - Projected Exascale and pre-exascale acceptance (2020-2025) ........................... 62 

Figure 17 - R&D investments in the race to Exascale ............................................................. 63 

Figure 18 – Areas of contribution of HPC to Sustainable Development Goals ...................... 76 

52 

 
 
Annex I: Market Analysis and Investments  

The economic impact of HPC 

The  worldwide  ICT  spending  in  2019  is  expected  to  near  EUR  5  trillion  in  2020,  of  which 
EUR 1 trillion will correspond to new areas closely linked to HPC technologies: the Internet 
of  Things  (IoT),  cybersecurity,  AI,  robotics  and  augmented  and  virtual  reality  techniques.74 
The business case behind commercial and industrial HPC use is relatively clear-cut. HPC use 
has  a  critical  impact  on  industries  and  businesses  via  advanced  modelling,  simulation,  and 
data analytics that address innovation challenges and support decision-making.  

Return on investment (ROI) of HPC 

The  economic  reach  of  HPC  into  the  industrial  infrastructure  of  the  most  developed 
economies is impressive, as this was shown in the EuroHPC JU Impact Assessment4. Among 
other findings showing that HPC is a key contributor in critical industry sectors for jobs and 
economic  output,  the  EuroHPC  JU  Impact  Assessment  showed  that  HPC  has  an  excellent 
return on investments (ROI) in scientific and industrial projects carried out within Europe.75,76 
In 2018, the results continued to indicate substantial returns for investments in HPC77:   

Figure 8 - Return on investments (ROI) of HPC 

Country 

Average of Profit or Cost Saving 
EUR  

Average of Revenue 
EUR   

per HPC EUR  

per HPC EUR  

China 

US 

EU 

Japan 

EUR 2.7 

EUR 35.1  

EUR 43.2 

EUR 223.2  

EUR 7.6 

EUR 336 

EUR 260 

EUR 1085.1 

The impact of HPC in GDP 

A recent study confirms the above, showing that HPC-reliant US economic sectors contribute 
almost 55% of GDP to the US economy, encompassing USD 9.8 trillion (EUR 9 trillion) in 
value. 78 

53 

 
 
 
Figure 9 - Secondary Impact of HPC on the US Economy 

By  analogy,  these  sectors  account  for  53.4%  of  the  EU  GDP,  and  encompass  EUR  7.56 
trillion in value.79 

“If  the  United  States  were  to  cede  global  competitive  advantage  in  yet 
another  technology  industry  (i.e.,  HPC),  it  would  mean  stiffer  economic 
headwinds for the U.S. economy and slower per-capita income growth.”126 

An update in the economic data confirms the growing importance of these critical sectors in 
the  EU  GDP  and  jobs.80  Six  of  the  most  important  economic  sectors  in  Europe 
(manufacturing, health and pharmaceuticals, automotive, oil and gas, aviation and chemicals) 
depend on HPC. They represented in 2018 more than 40% of the EU’s GDP and around 80 
million jobs. 

Examples of the economic importance of key sectors where HPC can make a difference 

  The car industry is one of the most HPC-dependent sectors, which in Europe provides jobs 
for 13.8 million people and accounts for 7% of the EU’s GDP (2018). HPC has enabled 
the  R&D  process  to  fully  abandon  early  prototypes  that  previously  required  costly 
customised  tools  and  machinery.  Although  some  physical  processes  such  as  crash  test 
simulations have not yet been fully replaced (partially due to regulatory demands), current 
HPC-supported prototypes are close to  serial  production. As the  ICT  component of cars 
increases, European carmakers are expanding their efforts to build the computing capacity 
they  need  as  vehicles  digitise  and  become  driverless.  In  fact,  they  are  now  hiring  more 
information technology specialists than mechanical engineers. 

  Weather:  the  weather  affects  33%  of  the  world’s  GDP.81  Every  year,  extreme  weather 
events have an estimated impact in Europe of EUR 400 billion, affecting around 5% of the 
European  population  and  causing  around  3000  deaths.  In  the  next  decades,  this  may  be 
worsen  and  2/3  of  European  citizens  could  be  affected  by  weather-related  disasters 
annually  by  the  period  2071-2100.82  Studies  foresee  that  if  no  further  action  is  taken  to 
tackle  climate  change,  the  combined  negative  effect  on  global  annual  GDP  could  be 
between 1.0% and 3.3% by 2060.83 In 1998-2017, the direct economic losses of disasters 
were valued at EUR 2617 billion, of which climate-related disasters caused EUR 2020.5 
billion  or  77%  of  the  total.  This  is  up  from  68%  (EUR  805.5  billion)  of  losses  (EUR 
1181.7  billion)  reported  between  1978  and  1997.  Overall,  reported  losses  from  extreme 
weather events rose by 151% between these two 20-year periods. 

54 

 
 
 
  The  health  and  pharmaceutical  sector  employs  almost  26  million  people  in  Europe  and 
represents 8.2% of the EU’s GDP. HPC is used in designing and simulating the effects of 
new  drugs  and  can  speed-up  the  diagnosis  and  treatment  of  diseases  including  cancer, 
cardiovascular diseases and Alzheimer’s disease.  

The HPC market 

(Unless specifically referenced otherwise, the data in this section come from different market 
analyses84  and 
the  study  (Impact  Assessment  Study  for  Institutionalised  European 
Partnerships  under  Horizon  Europe  -  Specific  Part  -  Candidate  Institutionalised  European 
Partnership in HPC)30. 

The worldwide market  for HPC has grown from about  EUR 1.8 billion in 1990 to  EUR 25 
billion  in  2018.  This  includes  the  following  categories:  servers,  storage,  software  and 
technical support. The forecast is that the overall HPC market will reach c. EUR 39.6 billion 
in 2023 for a CAGR of 7.2%. 2018 turned out to be an exceptionally good year for the HPC 
business. In particular, the global market for HPC servers grew by 15% from 2017 to 2018, 
reaching EUR 12.2 billion in revenues worldwide. This tendency is confirmed by the data of 
the first half of 2019, in which HPC server sales totalled EUR 6 billion.  

North America clearly leads the global market (i.e. purchases of HPC servers) with a c. 44% 
share, followed by EMEA (Europe, the Middle East and Africa) with around c. 30% (c. 26% 
for Europe only), and Asia/Pacific (c. 19%).  

Figure 10 - HPC Server market by region 

Overall, the record EUR 12.3 billion market for HPC servers in 2018 can be broken down in 
Supercomputers, Divisional HPC, Departmental, and Workgroup (see Figure 11). 

55 

 
 
 
Figure 11 - The Worldwide HPC server market 

The global HPC sales income by vendor in 2018 shows that on HPC supply, the USA is the 
absolute world  leader. The only sizeable  Europe-based vendor,  Bull-Atos, represents  only  a 
total market share of 1.1%, well under a peak market share of 5%, in 2011. 

Figure 12 – Global HPC Market by vendor shares 

Vendor 
HPE/HP 
Dell 
IBM 
Lenovo 
Inspur 
Sugon (Dawning) 
HPE/Cray 
Fujitsu 
Penguin 
NEC 
Bull Atos 
Other 
Total 

Country  2018 sales ($ million)  Share % 
34.8% 
4,766 
20.8% 
2,857 
7.1% 
971 
7.0% 
957 
5.8% 
788 
3.4% 
462 
2.3% 
313 
2.0% 
269 
1.8% 
244 
1.5% 
201 
1.1% 
150 
12.6% 
1,728 
100% 
13,706 

US 
US 
US 
China 
China 
China 
US 
Japan 
US 
Japan 
France 
- 

The worldwide forecast projects that HPC server revenues will grow to c. EUR 17.7 billion in 
2023  with  a  2018-2023  CAGR  of  7.8%.  This  2023  figure  includes  EUR  1.2  billion  for 
exascale supercomputers, EUR 2.4 billion for AI-dedicated HPC servers, and about EUR 4.9 
billion  in  cloud  usage  fees.  AI  will  be  the  fastest-growing  HPC  segment  for  HPC,  with  a 
projected 30% CAGR during the 2018-2023 period. 

Supercomputers category (systems over EUR 500K) 

The supercomputer category had a particularly robust year in 2018, increasing 23% compared 
with 2017 and reaching EUR 4.9 billion, the highest growing competitive segment of the HPC 
market. This tendency will continue in the following years: c. EUR 8.1 billion of expenditure 
are  in  the  pipeline  for  pre-exascale  and  exascale  systems  scheduled  to  be  installed  between 
2020 and 2025 worldwide. That  will provide a  big boost to  this category  and to  the overall 
HPC market over this timeframe.  

56 

 
 
 
 
 
However, in the strategically important high-end market of systems over EUR 2.25 million, 
the  current  situation  is  not  very  satisfactory.  The  Union  has  only  one  supercomputer  in  the 
top-1031  and  five  in  the  top-20  (November  2019),  dropping  from  a  peak  of  four  and  seven 
systems  respectively  in  2012.  Spending  levels  for  these  high-end  supercomputers  are  an 
important measure of HPC leadership. 

Europe and the HPC Market 

Integration  of  EU  suppliers  in  the  global  HPC  market  is  still  weak.  The  following  facts 
illustrate the scale of the problem: 

  On  HPC  supply  (all  segments),  the  US  is  the  world  leader  in  2018,  having  67%  of  the 

global HPC sales, followed by China (16.2%), Japan (3.5%) and the EU (c. 1.1%).  

  US  vendors  have  almost  100%  of  the  world-wide  processor  market,  with  Intel  holding 
more  than  95%  in  several  categories  of  processors  (CPU,  GPU,  etc.).85  No  European 
company supplies key components like general processor or accelerators. 

  Participation  of  EU  vendors  in  the  global  HPC  market  is  still  weak.  Out  of  all  top-500 
supercomputers, only 28 (5.6%) are supplied by EU manufacturers. 26 were supplied by 
one  main  EU  vendor  (Bull-Atos),  with  19  of  these  26  supercomputers  purchased  by 
clients in the EU and only 7 by other global clients. 

  Out of the 79 HPC systems in the top-500 list that are located in the EU, only 21 (26.5%) 
were supplied by European vendors. This  means that almost  75% of the  European HPC 
market is being supplied by non-EU manufacturers. 

 

In the top-500, Chinese vendors integrate around 65% of the systems. Chinese indigenous 
processors  are  present  in  only  a  few  of  those  systems,  but  it  is  expected  that  Chinese 
technology  for  the  exascale  supercomputers  will  likely  enter  the  market  in  the  next  few 
years. 

  Solutions based on open-hardware (in particular RISC-Vxxvi) are gaining momentum as a 
credible alternative to the proprietary solutions for processors and accelerators across the 
computing continuum. By 202186, a billion cores are expected to ship using the RISC-V 
architecture, growing to 62.4 billion cores in 2025 An interesting aspect of RISC-V is that 
any company can use it without any fear of losing access in the future (for instance due to 
commercial bans on technology exports).  

  RISC-V  will  create  opportunities  for  non-US  companies  to  break  the  almost  monopoly 
situation in chip design. China now has two of its own RISC-V industry alliances87 with 
more than 185 members (including Huawei, Sanechips from ZTE, Bitmain, Alibaba, and 
Xiaomi’s wearables partner Huami). The EU is  supporting RISC-V solutions  in  the EPI 
project and in other activities. 

 

Industries operating in weaker and less dense supply chains are generally less competitive 
and are more at risk of being taken advantage of by suppliers and clients, due to market 
power  being  concentrated  in  fewer  actors.  Companies  operating  in  these  environments 
also have a harder time sourcing and nurturing talent and scaling up their activities.  

  Historically, Europe has been strong in parallel software development and a global leader 
in exploiting HPC for innovation. The European share of the worldwide commercial HPC 

57 

 
 
software market closely matches its share of global spending in the HPC server market (an 
estimated 26% in 2018).  

Figure 13 - Vendors of systems installed in the EU 

Manufacturer 

Country 

China 
France 
US 
US 
Japan 
China 
US 
US/China 
China/US 
Netherlands/UK 

Japan/Germany 
Russia/US 

Lenovo 
Atos/Bull 
HPE/Cray 
IBM 
NEC 
Huawei 
Intel 
IBM/Lenovo 
Lenovo/IBM 
ClusterVision / 
Hammer 
NEC/MEGWARE 
T-Platforms, 
Intel, Dell 
Total 

N. 

35 
18 
10 
3 
2 
2 
1 
1 
1 
1 

1 
1 

76 

Uses of HPC with AI and Cloud 

HPC/HPDA and AI 

Three  major  forces  –  AI,  cloud  and  exascale  –  are  combining  to  raise  the  HPC  industry  to 
heights  exceeding  expectations.  Growth  has  been  driven  primarily  by  new  buyers  from  the 
enterprise  moving  into  HPC  for  AI-related  workloads,  such  as  fraud  detection,  business 
intelligence, affinity marketing, personalised medicine, smart cities and IoT. The convergence 
of HPC and big data  analytics is  being driven by  HPC users and the  growing contingent  of 
commercial  firms  that  are  adopting  HPC  solutions  to  tackle  data  analytics.  Worldwide  and 
European HPC server spending dedicated to HPDA will grow robustly. 

HPDA-AI is growing faster than the overall HPC market, and the AI subset is growing faster 
than HPDA, though in absolute figures it will remain smaller. By 2023, the overall HPDA-AI 
market  for  HPC  servers  will  reach  about  EUR  5.76  billion,  or  about  32%  of  the  EUR  18 
billion  worldwide  market  for  HPC  server  systems  with  a  five-year  CAGR  of  15.4%.  The 
subset  of  HPC-based  AI  (machine  learning  (ML),  deep  learning  (DL)  and  other  areas)  is 
expected to reach EUR 2.43 billion by 2023 for a 2018-2023 CAGR of 29.5%. 

The fastest-growing workloads are in AI (ML and DL). 87% of the surveyed cloud services 
providers  (CSPs)  and  94%  of  the  HPC  system  vendors  said  that  their  fastest-growing  HPC 
workloads are in the AI domain, more specifically ML and DL.  

Half  each  (50%)  of  the  CSPs  and  HPC  system  vendors  said  that  more  investment  is  also 
needed in simulation. For the foreseeable future, most HPC use will continue to be directed at 
modelling and simulation, and that simulation will play an important role in emerging AI use 

58 

 
 
 
 
cases.  For instance, the  RAND Corporation estimates88  that 8.8 billion miles of test  driving 
will  be  needed  for  consumers  to  acquire  95%  confidence  in  the  safety  of  autonomous 
vehicles,  and  that  physical  testing  this  many  miles  would  take  400  years.  Many  experts 
indicate  that  the  only  way  to  instil  confidence  in  5-10  years  is  with  simulation,  using  AI 
algorithms on high performance computers. 

HPC in the Cloud 

Worldwide, the proportion of sites exploiting cloud computing to address parts of their HPC 
workloads has grown to over 70% in 2019 –helping the "democratisation of HPC", especially 
as advances in virtualization capabilities becoming more efficient and HPC-friendly. This is 
of particular relevance for the potential links with European commercial initiatives such as the 
recently announced GAIA-X89, a new European data infrastructure project that aims to grow 
an autonomous and self-determined digital ecosystem in Europe. 
According to 2019 research from IDC90, the worldwide spending on public cloud services and 
infrastructure is expected to reach EUR 333 billion by 202291, a five-year CAGR of 22.5%. 
Cloud  has  been  slower  to  catch  on  in  HPC  circles.  Hyperion  Research  estimates  that  while 
70% of HPC sites run jobs in public cloud, these jobs comprise just 10% of all workloads. 

Recent surveys on HPC show cloud users reporting that they run 33% of their HPC workloads 
in  3rd-party  clouds.  The  HPC  community  runs  20%  of  workloads  in  cloud  environments. 
Despite the limitations of using HPC in  clouds (e.g. moving mission-critical  workloads  off-
premises  and  high  costs  associated  with  data  locality  where  large  volumes  of  data  are 
involved), 2019 is  a tipping point  year  for a significant  and long-anticipated shift  in  market 
attitudes  toward  running  HPC  workloads  in  clouds,  resulting  in  an  increase  in  the  revenue 
forecast from EUR 2.7 billion to EUR 3.6 billion for 2019 and totalling EUR 6.75 billion by 
2023.  This  reflects  a  compound  annual  growth  rate  (CAGR)  in  2018-2023  of  24.6%.  By 
applications,  HPC  in  the  cloud  will  be  led  by  geosciences  (27.3  %),  electronic  design 
automation  (26.0%),  and  biosciences  (25.6%)  bio-sciences,  followed  by  CAE  at  24.7%  and 
chemical  engineering  at  23.9%.  The  breakdown  also  shows  relatively  slower  cloud  growth 
(21.3%) for HPC performed in university/academic settings. 

A  study  of  HPC  end  users  that  are  currently  using  public  clouds  confirms  the  growing 
importance of third-party clouds from cloud services providers (CSPs) or system vendors to 
run  established  and  newer  HPC  workloads,  such  as  ML  and  DL.  On  average,  the  surveyed 
users run 33% of all their HPC work in third-party clouds; extrapolating from this  group of 
admitted cloud users to the whole HPC community drops that average to ~20%, representing 
a major uptick from the 10% figure in Hyperion Research surveys 18 months ago.  

HPC cloud computing is rounding a corner in the adoption curve. 40% of these users believe 
that all their HPC jobs could be run in the cloud – pointing to substantial headroom for cloud 
growth. The ultimate limiter of this growth may be data locality, the inefficiency of moving 
large  data  volumes  to  third-party  clouds  when  the  data  is  already  in  the  same  locale  as  the 
applications and computing resources. 

59 

 
 
Figure 14 – HPC in the Cloud market 

The study also confirms that the cloud segment should be seen as a complement to on-premise 
HPC computing, not as a threat. Most HPC work going to third-party clouds stems from pent-
up demand and users without on-premise HPC resources, not from jobs already being run on-
premise.  An  important  new  business  source  for  HPC  and  for  cloud  computing  includes 
commercial enterprises whose requirements are pushing up into the HPC competency space. 
CSPs and HPC system vendors have begun chasing these companies with increasing success. 

As just noted, 40% of the surveyed HPC users said all of their HPC workloads could be run in 
a  third-party  cloud  environment.  The  remaining  60%  of  HPC  users  disagreed,  saying  that 
some  of  their  HPC  workloads  are  not  suitable  for  being  run  in  an  external  cloud.  A 
coincidentally  similar  63%  of  surveyed  CSPs  reported  that  there  are  HPC  workloads  they 
advise customers not to run in the CSPs' cloud environments. Other recent Hyperion Research 
studies  and  interactions  with  major  CSPs  and  HPC  users  indicated  that  some  sites  keep 
mission-critical  and  secure  workloads  on-premise  as  a  matter  of  policy.  There  are  certainly 
other reasons for keeping some workloads out of external clouds, but the same sources point 
to data locality as the principal long-term reason for keeping certain workloads on-premise. 

HPC worldwide investments: the strategic race towards exascale computing 

Unless specifically referenced otherwise, the data in this section come from different market 
analyses84. 

Exascale computing: the opportunity for EU suppliers 

One  of  the  key  objectives  of  the  EuroHPC  JU  is  to  secure  a  European  autonomous  and 
competitive  HPC  technology  supply.  The  ambition  is  that  such  European  technology  may 
start  soon  being  integrated  in  the  future    European  HPC  infrastructure.  Representative 
examples of such efforts are the European Processor Initiative (EPI) and the other technology 
development activities launched in Horizon 2020.  

The  global  race  towards  exascale  gives  a  new  opportunity  to  the  EU  to  be  back  in  the 
computing  landscape.  Europe  has  all  it  takes  to  be  a  global  player  in  HPC  supply:  power-
efficient nano-electronics, interconnect and processor designs, middleware solutions, parallel 
programing  and  computing  resource  optimisation  solutions,  scientific  and  industrial  codes, 
etc.  Europe  can  exploit  its  strong  assets  in  order  to  get  European  industry  back  as  leading 

60 

 
 
 
technology supplier and reinforce its position as a world-leader in the use of HPC – Europe 
consumes around 30% of the world HPC resources but it only supplies 5% of these. 

A key goal of the EuroHPC JU efforts in the HPC supply is to leverage on technologies in the 
computing  continuum.  The  development  of  European  technologies  is  not  for  the  sake  of 
building the fastest supercomputer in the world (a "one of a kind" system), but rather to build 
"first of a kind" systems with technologies that reach beyond the HPC domain and feed the 
broader ICT markets in the longer run with EU-made technologies. The transition to exascale 
computing  represents  the  opportunity  for  the  European  supply  industry  to  leverage  on 
technologies in  the computing continuum.  These technologies have a wide application area, 
from  smart  phones,  to  embedded systems  (for example in  the future driverless  cars),  and to 
data servers, feeding a broader ICT trillion-market within a few years of their introduction in 
high-end HPC.  

There is a huge potential economic effect in the mass computing market from the investments 
in HPC technologies: HPC leadership can provide a “first mover” advantage; the technologies 
and  skills  needed  to  design,  develop,  and  deploy  leadership  class  systems  often  lead 
requirements  for  other  computing  systems  by  many  years.  Understanding  and  driving 
innovations at the leading edge can enable a valuable learning curve for the leaders; reacting 
to these innovations can be expensive and can lead to loss of markets by the incumbents to the 
innovators.  

Between  today  and  2025,  major  government-sponsored  efforts  will  drive  development  of 
about 26 near-exascale and exascale systems, with total spending of about EUR 8.1 billion (in 
the  range  of  EUR  0.9  to  EUR  1.8  billion  per  year).  China  may  be  the  first  to  install  an 
exascale system within the next 18 months, with the USA following soon afterward with the 
installation  of  Aurora  supercomputer.  Japan  will  field  the  first  $1  billion  (EUR  0.9  billion) 
supercomputer ever, the Fugaku system. 

61 

 
 
 
Figure 15 - Projected Exascale Systems dates 

Figure 16 - Projected Exascale and pre-exascale acceptance (2020-2025) 

The projected levels of R&D investment associated for the development of the above systems 
(in addition to the purchase investments) are also summarised here (November 2019): 

62 

 
 
 
 
Figure 17 - R&D investments in the race to Exascale 

The  exascale  plans  for  the  US  and  China  are  particularly  interesting,  in  as  much  as  both 
countries will probably be deploying the largest number of these systems over the next several 
years.  If the projected performance estimates are accurate, not all will achieve 1 exaflops on 
Linpack.  Two  of  the  first  three  American  exascale  systems  are  expected  to  be  delivered  by 
late  next  year,  with  acceptance  in  2022.  These  are  Aurora,  comprised  of  the  Cray  Shasta 
architecture  with  Intel  Xeons  and  Intel  Xe GPUs  for  Argonne  National  Laboratory;  and 
Frontier, comprised of Cray Shasta and AMD Epyc CPUs and future Radeon GPUs for Oak 
Ridge National  Lab. The third system, El Capitan, based on the Cray Shasta architecture, is 
expected  to  be  delivered  to  Lawrence  Livermore  National  Lab  within  two  years,  with 
acceptance in 2023. 

63 

 
 
 
Annex II: HPC and AI 

AI is globally recognised as one of the most strategic technologies of the 21st century, thanks 
to the growth in computing power, availability of data and progress in algorithms. The recent 
advances in digital technologies reflect the increasing importance of the convergence of HPC, 
AI  and  big  data,  representing  a  fundamental  transforming  evolution  of  the  use  of  HPC  for 
scientific,  industrial  and  policy-making  applications.  This  evolution  can  be  characterised  in 
the three stages of the use of HPC:  

  Modelling  and  simulation  are  reducing  the  need  for  costly  and  time-consuming 
experiments or physical prototypes, and allow the study of properties that are impossible 
to test experimentally.  

  High  performance  data  analytics  (HPDA)  combine  HPC  with  data  analytics,  involving 
parallel  processing  of  huge  amounts  of  data.  This  provides  much  deeper  insights  into 
previously unexplored areas and systems of the highest complexity. 

  Convergence  with  AI:  The  newest  AI  developments  such  as  ML  and  DL  are  made 
possible  by  the  increasing  availability  of  sufficient  amounts  of  training  data,  huge 
processing HPC power and new algorithms exploiting such computing power. 

“Deep  learning  has  been  a  game-changer  for  AI  with  a  tremendous 
improvement  in  performance  for  specific  tasks  such  as  image  or  speech 
recognition,  or  machine  translation.  ….  Significant  advances  in  these 
technologies  have  been  made  through  the  use  of  large  data  sets  and 
unprecedented computing power.”93 

HPC for AI: AI needs  HPC not only to execute the specific computing tasks of processing 
data  but  also  for  building/feeding  the  computational  model  for  AI  tasksxli.  HPC  generates 
huge amounts of data suitable for AI training. HPC can scale up the learning phase of neural 
networks  providing  for  example  the  computing  power  for  implementing  unique  levels  of 
parallelism for massive scaling of Deep Neural Network training92, or for the auto-tuning of 
the  choice  of  models  (Auto  DL  and  ML).  HPC  is  also  critical  to  generate  trust  for  AI, 
providing  explicability  techniques  and  implementing  tools  for  the  coupling  between  formal 
methods and neural networks. 

AI for HPC: HPC (and HTC) need also AI. There is a wide range of AI techniques helping 
HPC  powered  tasks  and  applications,  for  example:  inferring  data  flows  from  large  scale 
scientific  instruments  (stream  access,  support  of  end  to  end  workflows),  coupling  learnt 
models  and  simulation  codesxlii  aiming  at  cognitive  simulation,  for  (in-situ,  in-transit)  post 
processing of numerical  simulations (optimising data movement and minimising energy), or 
for  better  exploiting  systems  and  computing  centres  (with  AI  driven  schedulers,  preventive 
maintenance, optimisation of the infrastructures, etc…). 

One  of  the  challenges  at  medium-term  will  be  to  achieve  the  optimum  trade  where  HPC 
supports the efficient running of both compute-intensive and data-intensive workloads. This is 
called-off  between  the  precision  of  the  AI  models  and  the  associated  computational  cost, 

xli  Data from GENCI (Grand équipement national de calcul intensif), France. 
xlii    The  ACM  Gordon  Bell  prices  2018  to  recognise  outstanding  achievement  in  HPC  awarded  two  HPC 

applications enhanced with AI techniques. 

64 

 
 
                                                 
especially  in  IoT  applications  or  scenarios  with  real  time  requirements,  where  latencies  are 
critical.  

The HPC/AI synergies are emerging in many different domains. This can be illustrated in the 
following three areas:  

1.  Digital transformation of Europe and industrial applications 

The  synergy  between  and  HPC  and  AI  technologies  is  of  capital  importance  for  the 
digitisation of Europe. The Commission in its Communication “Artificial Intelligence for 
Europe”93 proposes the set-up of industrial data platforms offering high quality datasets in 
several  application  areas  and  the  development  of  a  single  access  point  for  all  users  to 
relevant AI resources in the EU, the "AI-on-demand platform". In addition to data, tools 
and  algorithms,  this  initiative  will  offer  the  necessary  HPC  power  to  analyse  the  huge 
amounts of data and execute the advanced tools and algorithms necessary to fully exploit 
the AI potential. 

The  digitisation  of  industry  is  bringing  a  revolution  in  the  way  business  operate.  The 
combination of computing with AI enables the 4th industrial revolution – “Industry 4.0”. 

“We're  in  the  midst  of  a  significant  transformation  regarding  the  way  we 
produce products thanks to the digitization of manufacturing. This transition 
is so compelling that it is being called “Industry 4.0” to represent the fourth 
revolution  that  has  occurred  in  manufacturing.  From  the  first  industrial 
revolution  (mechanization  through  water  and  steam  power)  to  the  mass 
production  and  assembly  lines  using  electricity  in  the  second,  the  fourth 
industrial revolution will take what was started in the third with the adoption 
of  computers  and  automation  and  enhance  it  with  smart  and  autonomous 
systems fuelled by data and machine learning.”94 

AI technologies  require  more and more computing power and data to  perform  advanced 
real-time  analytics  and  create  new  high  added-value  business,  services  and  applications. 
The  combination  of  HPC,  big  data  and  AI  is  the  key  to  enhance  product  quality, 
understand  customer's  behaviours,  and  react  to  unforeseen  events  much  faster,  bringing 
innovation and new jobs and opportunities.  

This  development  in  the  industrial  arena  in  the  last  few  years  has  been  made  possible 
thanks to the increase of the “raw” computational force easily available, the exponential 
amount of data, and the enhanced abilities of AI techniques (in particular ML and DL) to 
learn and leverage information from such data. This is making supercomputers a necessity 
in a very broad range of industries such as biotechnology, finance, manufacturing, or oil 
and gas exploration. 

This market trend is bound to continue as shown in Annex I. The technology combination 
of HPC and AI is fostering the rapid development of new applications and HPC services 
across  multiple  industrial  sectors,  not  only  in  emerging  markets,  but  also  in  the  more 
traditional parts of the economy, in particular if such services are available in secure and 
easy-to-use cloud-based platforms.  

2.  Scientific applications 

As  early  adopters  of  the  HPC  technology  since  the  1990s,  the  use  of  HPC  in  scientific 
applications illustrates the evolution of the use of supercomputing that is being perceived 

65 

 
 
more  recently  in  other  industrial  and  policy-making  areas:  modelling  and  simulation, 
HPDA, and extensive use of AI techniques.  

The convergence of HPC with AI and big data is shaping a revolution in many scientific 
areas  –to  the  extent  that  some  qualify  already  the  “data  science”  as  the  fourth  pillar  of 
scientific method. Again, the most visible results of this confluence are found in the life 
sciences  and  medicine.  In  a  few  years,  personalised  medicine  will  become  mainstream 
medicine,  with  diagnosis  and  treatments  tailored  both  to  the  patient  and  the  state  of  the 
disease,  and  it  will  support  medical  analysis  and  decision-making,  e.g.  ML  algorithms 
supporting  the  online  analysis  of  X-rays  with  millions  of  other  samples  for  general 
practitioners, or real-time support in operations.  

3.  Security and Cybersecurity  

Security 
HPC and AI are game changing applications in security95 and both the US and China have 
already linked closely HPC and AI developments in their programmes. 

US: The US  President  Trump's executive order on Maintaining American  Leadership in 
Artificial  Intelligence47  makes  explicit  the  HPC-AI  link,  asking  his  administration  to 
prioritise  the  allocation  of  high-performance  computing  resources  for  AI-related 
applications.  The  US  2020  budget  request96  proposes  cuts  in  many  science  programmes 
but  increases  the  HPC  funding  of  the  Department  of  Energy  (DoE),  in  charge  of  the 
federal HPC national laboratories that will be hosting the exascale US supercomputers and 
the  Exascale  technology  developments.  The  DoE  budget  includes  substantial  specific 
budget  lines  for  AI  (EUR  107  million),  complementing  the  EUR  728  million  for  the 
Exascale Computing Initiative.  

China:  As  the  second  biggest  ‘player’  in  general-purpose  AI,  China  is  increasingly 
showing that it is capable of keeping pace with the US in this field. The overarching goal 
is to “boost China's overall competence in AI”. These developments are catalysed by an 
HPC industry, which is increasingly self-reliant: after the US government banned the sale 
to  China  of  Intel  Xeon  processors  in  April  2015,  China  was  able  to  substitute  its  own, 
native-built  processors  in  the  design  of  the  Sunway  Taihu  Light,  the  world's  fastest 
supercomputer from 2016 to 2017. 

Cybersecurity 

In cybersecurity, HPC unlocks the power of security tools thanks to its capability to speed 
up the AI- and ML-driven complex software. Hybrid techniques combining HPC and AI 
(in  particular  ML  techniques)  are  used  for  a  more  effective  threat  analysis  and  security 
event  correlation.  Novel  techniques  are  developed  every  day  using  these  hybrid  tools, 
detecting  strange  systems  behaviour,  insider  threats  and  electronic  fraud;  detecting  and 
fighting very early cyber-attack patterns (in a matter of few hours, instead of a few days) 
or potential misuse of systems, allowing for automated and immediate actions even before 
hostile events occur.  

"By  2025,  machine  learning  will  be  a  normal  part  of  security  practice  and 
will  offset  some  skills  and  staffing  shortfalls."  Gartner  further  states:  "We 
can't escape the fact that humans and machines complement each other, and 
together  they  can  outperform  each  alone.  Machine  learning  reaches  out  to 

66 

 
 
humans  for  assistance  to  address  uncertainty  and  aids  them  by  presenting 
relevant information."97 

Hybrid  HPC/AI  is  a  security  asset  for  companies  to  deal  with  the  ever-worsening 
sophisticated  attacks.  For  example,  advanced  persistent  threats  are  long-term  attacks 
performing  continuous  stealthy  computer  hacking.  The  undetected  attacks  linger  inside 
systems  for  weeks  or  months,  moving  across  corporate  infrastructure  and  getting  past 
security controls. Highly accurate and rapid event correlation and anomaly detection can 
help  uncover evidence of such attacks. HPC/AI-powered security tools give a long-term 
advantage to organizations defending against cyberattacks.  

European examples of the convergence of HPC/AI use 

The  combination  of  HPC  with  AI-based  methods  has  a  huge  transformative  impact  in  the 
processing  and  the  extraction  of  added  value  from  massive  amounts  of  data,  in  particular 
using ML/DL approaches. Between AI and more traditional HPC modelling there is a positive 
feedback that can further accelerate both techniques. For example, simulations produce huge 
amounts  of  data  to  train  the  AI-based  algorithms,  and  AI  techniques  accelerate  the 
parameters/phase space exploration to find optimal solutions to the simulated problems. There 
are several examples illustrating this important transformative impact in Europe: 

ANTAREX and Exscalate4CoV 
ANTAREX98  is  an  example  of  how  AI  and  HPC  can  substantially  boost  Computer  Aided 
Drug Discovery: 

Antarex produced a platform “Exscalate” capable of speeding up 100 times faster the drug 
discovery  process,  using  AI  and  HPC  combined  techniques.  ANTAREX  use  the  Marconi 
supercomputer (ranking #21 in the world) to run exascale-ready HPC/AI technologies to help 
shorten the path from the discovery of a health threat to the availability of a cure. 

An  Italian  pharma  SME  (Dompé)  is  now  able  to  optimise  molecular  docking  to  reduce  the 
virtual  screening  process  for  the  identification  of  new  active  substances  by  two  orders  of 
magnitude. This is the most important use case to test the ANTAREX technologies, helping 
to produce novel treatments against the Zika pandemic.  

  A 

total  of  1.2  billion  molecules  (including  all 

investigational  and  marketed 
drugs) targeting the Zika virus were screened and virtually tested using a massive parallel 
simulation  in  Marconi.  This  makes  it  the  largest  virtual  screening  experiment  ever 
launched in terms of computational threads (1 million) and database size (1.2 billion). 

  The  new  computational  techniques  in  the  Dompé  software  resulted  in  the  following 
savings: time to solution from 52 to 3.5 days; energy consumption from 504 to 84 MWh; 
and, cost to solution from EUR 70 K to EUR 12 K. 

ANTAREX helped Dompé to become worldwide competitive, running faster & greener, with 
a new process that paves its way to grow from SME to large industry. 

A  spin-off  result  of  ANTAREX  has  been  the  EU-funded  supercomputing  project 
“Exscalate4CoV”99  that  exploits  high-performance  HPC  and  artificial  intelligence  (AI) 
technologies  that  complement  traditional  biology  methods  to  find  a  treatment  for  the  novel 
coronavirus disease (see Annex III, section “HPC and the COVID-19 crisis” for more detail. 
The Human Brain Project Flagship100 

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The aim of the “Human Brain Project” (HBP) FET Flagship is to understand the functioning 
of the human brain. HBP is using large-scale simulation and multi-scale modelling to produce 
a  detailed  3D  map  of  the  brain  derived  from  many  thousands  of  histological  brain  slices 
imaged at ultrahigh resolution with modern microscopes.  

Mapping  brain  areas  is  a  very  time  consuming,  semi-automatic  process  that  involves 
analysing complex patterns of cell distributions in different independent subjects.  

Scientists  aim  at  creating  a  new  generation  of  brain  mapping  tools  that  exploit  the  most 
advanced high-throughput imaging devices, ML algorithms and HPC infrastructures available 
today.  They  have  trained  a  deep  convolutional  neural  network  to  classify  texture  in 
microscopic scans of brain tissue into different brain areas. The network learns precise texture 
features  from  existing  annotations  in  microscopic  images,  and  combines  them  with 
information from existing atlases. The neuroscientists and data analysts have worked closely 
with  the  JUELICH  supercomputing  centre  to  run  the  application  at  scale  on  the  GPU-
accelerated clusters JURECA and JURON. The use of this modern HPC infrastructure enables 
the algorithm to process many large chunks of image data in order to capture both the cellular 
detail and spatial context. Without HPC, running the network would be almost infeasible.  

Pl@ntNet 
Pl@ntNet101 is an identification system that helps you identify plants through images. It 
is  a research and a  citizen science project,  initially supported by Agropolis  Foundation, and 
developed since 2009 within the framework of a consortium bringing together Cirad, INRA, 
INRIA,  and  IRD.  Pl@ntNet  is  available  for  free  as  an  app  on  the  AppStore  and  on  Google 
Play, and is since its launch in February 2013 the application has more than 12 million users. 

The Pl@ntNet system works by comparing visual patterns transmitted by users via photos of 
plant organs (flowers, fruits, leaves ...) that they seek to determine. These images are analysed 
and  compared  using  ML/DL  techniques  to  an  image  bank  produced  collaboratively  and 
enriched  daily.  The  system  then  offers  a  possible  list  of  species  with  its  illustrations.  This 
research is at the frontier of several fields (botany, ecology, computer science, citizen science) 
and aims in particular to contribute to the monitoring of plant biodiversity (more  than 369K 
species of flowering plants in the world) on a global scale, thanks to the involvement of the 
citizens of the planet. They are every day more than 140,000 users of the application around 
the world. The system currently works on more than 20,000 wild plants and ornamental and 
cultivated plants. 

The HPC resources are provided by GENCI and are helping in the improvement of the tools. 

CALIOPE 
CALIOPE102 is the system developed by the Barcelona Supercomputing Centre (BSC) which 
offers  48-hour  air  quality  forecasts  for  Spain  and  Europe,  thanks  to  the  combination  of 

68 

 
 
 
different numerical simulation models (meteorology, emissions and photochemical transport) 
executed by the MareNostrum Supercomputer and AI techniques.  

CALIOPE  analyses  the  air  quality  in  a  given  area  and  the  concentrations  of  the  main  air 
pollutants  (ozone,  nitrogen  dioxide,  sulphur  dioxide,  and  particles),  providing  the  citizens 
with a reliable forecast of air quality in the 24-48 hour range. Examples: 

  For Barcelona, CALIOPE provides decision makers with the information they need take 
preventive  action,  providing  forecasts  that  incorporate  different  emission  reduction 
scenarios such as vehicle bans; 

  For  Mexico  City,  citizens  have  access  to  predictions  of  the  presence  of  the  main 
atmospheric pollutants 24 hours in advance, and in resolutions accurate to one km2 and to 
the hour. The system will be complemented with predictions of the effects of the various 
measures  and plans that  the government  may  consider (emission reduction programmes, 
crisis management, etc.). 

CALIOPE will further develop the use of AI to  combine high resolution video-based traffic 
data with instantaneous emission models to improve predictions and propose better scenarios 
IoTwins103  

Digital  twins  is  a  prefect  case  for  the  combination  of  HPC,  AI,  IoT  and  Big  data.  IoTwins 
combines  complex  HPC,  Big  Data  and  ML  techniques  to  help  repositioning  the 
manufacturing industrial processes in Europe and make them more efficient and competitive. 
The  testbeds  under  development  will  show  the  advantages  of  adopting  digital  twins  in  the 
different application domains. 

Globally  more  and  more  producer  goods  are  planned,  calculated,  designed  and  simulated 
digitally.  IoTwins is a unique and flexible platform for the creation of industrial digital twins. 
Within the project there will be 12 testbeds, each realizing a digital twin. 
CERN104 

Physicists use the 26.7-km Large Hadron Collider (LHC) tunnel to accelerate particles almost 
to light speed, smash them together and analyse the resulting shower of particles. Collisions in 
the LHC generate particles that often decay in complex ways into even more particles. Up to 
about  1  billion  particle  collisions  can  take  place  every  second  inside  the  LHC  experiment's 
detectors. It is not possible to read out all of these events. A 'trigger' system is therefore used 
to  filter  the  data  and  select  those  events  that  are  potentially  interesting  for  further  analysis. 
Only  around  0.004  percent  of  the  total  data  generated  is  kept.  Even  after  the  drastic  data 
filtering, the CERN Data Centre processes on average one petabyte of data per day. The LHC 
experiments  produce about  90 petabytes of data per  year, and an  additional 25 petabytes of 
data are produced per year for data from other (non-LHC) experiments at CERN.  

The High-Luminosity LHC, the successor to the LHC, is planned to come online after 2025. 
By this time, the total computing capacity required by the experiments is expected to be 50-
100 times greater than today, with data storage needs expected to be in the order of exabytes. 

All  this  imposes  huge  computational,  storage,  and  analytic  requirements.  Two  examples 
illustrating the combination of advanced HPC, data and AI techniques are the following: 

  CERN  demonstrated  that  AI-based  models  have  the  potential  to  act  as  orders-of-
magnitude-faster  replacements  for  computationally  expensive  tasks  in  simulation,  while 
maintaining  a  remarkable  level  of  accuracy.  The  time  to  create  an  electron  shower  is 

69 

 
 
reduced from 17000 milliseconds in the full simulation to only 7 milliseconds with the AI 
trained model – this has a very important impact in the LHC's worldwide distributed CPU 
budget,  in  which  most  of  the  half  a  million  CPU-years  equivalent  is  dedicated  to 
simulation. This kind of approach could help to realise similar orders-of-magnitude-faster 
speedups for computationally expensive simulation tasks used in a range of experiments 
in current and future accelerators. 

  CERN recently adopted two new innovations  employing ML for the enhanced detection 
and analysis of elementary particles: ML techniques can recognise specific patterns in the 
billions  of  particle  collisions  that  occur  every  second  in  the  LHC,  with  innovative 
algorithms to identify the different types of quarks in the detector. These techniques can 
also  increase  the  sensitivity  of  the  data  analysis  when  comparing  the  results  and  thus 
verify theoretical models faster, to distinguish between them and, in some cases, exclude 
large  numbers  of  new  physics  models  from  the  measurement  results.  This  permits  to 
understand which unknown phenomena are still overlooked today. 

Weather at ECMWF and MeteoSwiss105 

Climate  modelling  and  weather  prediction  is  a  major  application  of  HPC  systems  for 
delivering  socio-economic  benefits  through  advanced  weather  and  climate  forecasts.  The 
European  Centre  for  Medium-Range  Weather  Forecasts  (ECMWF)  uses  approximately  40 
million observations daily in their models. For climate modelling, a single 30-year run from a 
25  km  resolution  model  produces  in  the  order  of  10  Terabytes  of  multivariate  data.  For 
numerical weather prediction (NWP) or climate modelling, the data is fitted to fill a 3-D grid 
over which multiple simulations are run over time.  

With constantly changing weather patterns and a warming climate,  weather forecasters need 
to  have  improved  prediction  capabilities  that  extend  across  time  and  that  provide  higher 
resolutions  going  down  to  a  few  kilometres.  Supercomputers  play  a  vital  role  due  to  their 
massive compute resources, but is not enough. While there is a 5x fold increase in data that is 
expected to happen by 2020, a 1,000x fold increase in the model complexity is expected. 

The  use  of  ML  techniques  help  improve  the  use  of  HPC  resources  to  enhance  parallelism. 
MeteoSwiss,  the  Swiss  meteorological  office,  has  successfully  run  ML/DL  techniques. 
MeteoSwiss has seen a 40x performance boost and a 3x power consumption reduction, with 
finer  1  km  resolution  and  a  forecast  that  can  be  updated  every  3  hours.  This  was  done  by 
porting  traditional  simulation  codes  to  fit  an  accelerated  GPU-based  cluster  that  allows  an 
effective execution of DL and AI techniques. 

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Annex III: Applications of HPC  

This section completes and illustrates in more detail section 3.1 “The increasing importance 
of HPC for a wide range of applications”. 

The data revolution and the strategic digital autonomy  

HPC has key role in our industrial, scientific, and societal development. HPC impacts almost 
every aspect of our daily life. The Impact Assessment for EuroHPC2 analysed the global use 
of HPC with more than 800 applications across all scientific fields, branches of government 
and virtually all industries and sectors.   

The  convergence  of  HPC,  AI,  big  data  and  high  performance  data  analytics  (HPDA),  and 
Cloud  is  the  main  innovation  driver  in  the  “data  revolution”,  creating  entirely  new 
possibilities  to  extract  useful  and  usable  knowledge  from  the  huge  amount  of  raw  data 
produced every day50. By 2020, the entire digital universe is expected to reach 44 zettabytes 
(1021), i.e. the equivalent of 5.6 trillion (1012) bytes per human on the planet. And, by 2025, 
it's estimated that 463 exabytes (1018 bytes) of data will be created each day –the equivalent 
of around 213 million DVDs per day. 
HPC is at the core of the Digital Single Market strategy106. It is the “engine” that powers the 
data revolution, and a key element to fulfil the ambition of putting Europe in the driving seat 
of  the  global  data  economy.  HPC  is  the  enabler  of  novel  leading-edge  technologies, 
applications  and  solutions  that  open  new  opportunities  for  digitising  European  science, 
industry and public authorities, benefiting all areas of the economy and society.  
In the Impact Assessment of the EuroHPC2 an analysis was provided of the current situation 
and importance of HPC for the digital autonomy. In a nutshell, the Union currently depends 
ever  more  on  foreign  supply  of  key  technological  components  for  its  supercomputing 
infrastructure, making it vulnerable to changes in commercial or geostrategic policies of our 
world competitors. The European HPC technology supply chain is weak and the integration of 
European  technologies  into  operational  HPC  machines  remains  insignificant.  This  has 
important consequences: 

–  Lack of strategic knowledge in the Union for innovation and competitiveness;  

–  Data  produced  by  EU  research  and  industry  is  processed  elsewhere  because  of  lack  of 

corresponding capabilities in the EU.  

–  European  researchers  and  innovators  may  move  to  those  areas  of  the  world  where  high 

data and computing capacity is available.  

Dependency  on  non-European  resources  and  knowledge  represents  a  clear  risk  for  Europe's 
technological  autonomy  and  scientific  and 
leadership,  with  wide-ranging 
consequences in security, privacy, data protection, commercial trade secrets, and ownership of 
data in particular for sensitive applications. 

industrial 

“In many ways, control of computing equals control of information. What if 
the  personal  email  and  social  networks  of  a  sizable  portion  of  U.S.  citizens 
are hosted overseas? … The emerging Internet of Things has the potential for 
providing a variety of innovations that could increase quality of life, but, in 
doing so, exponentially increase the amount of sensitive digital information: 
medical  conditions  from  wearable  diagnostic  devices,  audio  from  always-

71 

 
 
listening artificial intelligence assistants, activity information from an array 
of connected sensors in homes and in businesses. The use of HPC by foreign 
entities to analyse the data acquired by these systems is a potential threat to 
individual and societal privacy.”107 

HPC and industry’s innovation potential  

HPC is a mainstream technology for the digitisation of industry. The use of HPC is expanding 
to  all industries as it becomes more  accessible with today's and  future broadband networks. 
HPC  has  traditionally  enabled  industrial  sectors  that  are  “computationally  aware”  like 
manufacturing  to  move  up  into  higher  value  products  and  services.  In  particular,  the  use  of 
HPC services over the cloud will make it significantly easier for SMEs that do not have the 
necessary financial means to invest in their in-house HPC infrastructure to make use of HPC 
capabilities in order to develop and produce better products and services. 

At European level, there are several successful examples of programmes supporting industrial 
access  and  collaboration  based  on  HPC  capacities.  For  example,  the  PRACE  Industry 
Access108  provides  dedicated  resources  from  the  PRACE  supercomputers  to  industrial 
projects, aiming at increasing the industrial uptake of HPC in the Tier-0 PRACE systems. The 
HPC  Centre  of  Excellence  for  Engineering  Applications  (Excellerat)109  supports  key 
engineering European industries to use HPC in highly complex applications. The HPC Centre 
of  Excellence  for  Performance  Optimisation  and  Productivity  (POP2)110  provides 
performance optimisation and productivity services for academic and industrial code(s) in all 
domains. 

HPC and digital twins 

Digital twins are exact digital replica of physical entities, products, real processes, and plants 
that  interact  with  each  other.  They  can  reflect  static  properties  as  well  as  the  evolving 
behaviour.  Through  the  collection  of  large  amounts  of  data,  they  can  simulate  different 
scenarios to define corrective actions, optimise efficiency and diagnose anomalies before they 
occur.  Digital  twin  can  play  a  radical  transformative  role  for  the  digitisation  of  European 
industry:  

For  example,  the  digital  twin  of  an  automobile  prototype  is  a  digital,  3D 
representation of every part of the vehicle, replicating the physical world so 
accurately that a human could virtually operate the car exactly as he or she 
would in the physical world and get the same responses, digitally simulated. 

Companies are using these “digital twins” in a growing number of industrial sectors, making 
it easier to design and operate complex products and processes ranging from wind turbines to 
supermarket  aisles.  Three-dimensional  (3D)  digital  twins  were  originally  made  for  product 
design and simulation to optimise the product lifecycle. IoT solutions were then incorporated 
to generate real-time feedback between physical objects and their digital counterparts.  

Digital  twins  can  bring  enormous  value  to  companies:  the  time-to-market  is  shortened 
drastically,  because  the  digital  twin  can  generate  data  throughout  the  complete  life-cycle 
before  the  real  product  is  launched;  and  conclusions  regarding  the  condition,  usage,  error 
sources and more can be made and used to develop new and better products.  

HPC  is  enabling  a  new  class  of  digital  twins.  Many  companies  have  already  derived 
immense value from digital twins. Yet, these traditional digital twins are limited in that they 
cannot work on physical and virtual models simultaneously. A new generation of digital twins 

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requires  the  powerful,  agile  computing  capabilities  provided  by  HPC  to  facilitate  global 
mobility  and  collaboration,  combining  different  technologies  such  as  mixed  reality  tools, 
cloud  rendering, real-time simulation  and analysis,  IoT and DL/AI. These new digital  twins 
are able to significantly accelerate the product development and manufacturing processes, by 
generating digital representations of their end-to-end business processes while providing new 
ways of collaborating simultaneously in the virtual and physical world.111 

Digital  twin  adoption  and  market  size  will  continue  to  increase  exponentially  twin 
adoption.112  113 Adoption  of digital  twins across products,  machines and processes continues 
to  skyrocket  across  enterprises.  Deloitte forecasts the  global  market  for  digital  twin 
technologies will reach EUR 35 billion by 2025. By 2022, 40% of IoT platform vendors will 
integrate simulation platforms, systems and capabilities to create digital twins. 30% of global 
2000 companies will be using data from digital twins of IoT connected products and assets, 
achieving  gains  of  up  to  25%.  70%  of  manufacturers  will  use  digital  twins'  to  conduct 
simulations and scenario evaluations, reducing equipment failure by 30%114.  

SMEs 

The use of HPC resources has recently come into reach for many SMEs. Until approximately 
five years ago, the use of HPC resources had been considered too complex, costly and hence 
out of reach for many smaller businesses. This was largely attributed to the lack of software 
integration and limited cloud capacity for running HPC applications and providing users with 
easily accessible HPC services. There are, however, continuing barriers to the effective use of 
HPC by SMEs due to constraints related to access to adequate software packages that suit the 
specific needs of SMEs.44 

The  HPC  specific  activities  for  the  SMEs  that  Horizon  2020  supports  show  that  there  is  a 
growing demand of SMEs as new users of HPC: 
  The Fortissimo and Fortissimo-2 actions37 were highly successful in attracting new SME 
users to advanced cloud-based HPC solutions based on modelling and simulation and/or 
HPDA. Fortissimo demonstrated the feasibility of setting up a “market place” of "one-stop 
shop"  where  all  necessary  skills  and  services  along  the  simulation  value  chain  for  HPC 
and  HPDA  would  be  easily  available  and  affordable  on  a  pay-per-use  basis  for 
manufacturing SMEs. Fortissimo estimates that about 30 000 SMEs in Europe are likely 
to benefit from such a marketplace.  

  SHAPE44 is a pan-European programme supporting SMEs to adopt HPC and is supported 
by  the  HPC  resources  provided  by  the  HPC  infrastructure  of  PRACE.  SHAPE  aims  to 
raise awareness and equip European SMEs with the expertise necessary to take advantage 
of  HPC-enabled  innovation  possibilities,  thus  increasing  SMEs  innovation  potential. 
SHAPE helps European SMEs overcome barriers to use HPC, such as cost of operation, 
lack of knowledge and lack of resources, and facilitates the process of defining a workable 
solution based on HPC and defining an appropriate business model. 

The ambition in EuroHPC will be to develop further the strategies put forward by Fortissimo, 
the HPC Competence centres, PRACE SHAPE, SESAMENet70, Enterprise  Europe Network 
and  Digital  Innovation  Hubs  to  enhance  the  HPC  uptake  by  SMEs.  Ensuring  fairness,  in 
particular  with  regards  to  the  ease  of  access,  access  time  and  the  pricing  of  pay-per-use 
access, will be decisive in achieving a broader uptake of HPC in SMEs. 

On  the  other  hand,  evidence  on  excess  demand  from  industry  is  somewhat  ambiguous.  A 
study  conducted  by  the  EIB29  notes  that  HPC  customers  in  Europe  are  primarily  public 

73 

 
 
entities  in  research  and  academia.  These  are  accounting  for  approximately  90-95%  of  the 
operating  time  on  Europe's  highest  performing  systems  and  only  the  remaining  5-10%  is 
installed for private use. The main commercial users of HPC are large corporations while the 
uptake  amongst  SMEs  is  limited,  mainly  due  to  lack  of  awareness  of  the  benefits  of  HPC, 
technical knowledge barriers, and the considerable capital  costs required.  Digital  Innovation 
Hubs and Enterprise Europe Network will have an active role to play in reaching out to SMEs 
to promote HPC and its benefits and to encourage, guide, and facilitate SME access to HPC. 
There is a trend towards HPC centres gradually opening up to cooperation with industry, and 
some  of  the  frontrunners  have  been  operating  successful  industrial  outreach  programmes  to 
work with the private sector. These centres partly finance themselves via these activities, but 
the  EIB  has  noted  that  some  public  HPC  centres  lack  viable  business  models  due  to  legal 
limitations in raising revenues from commercial activities. 

Scientific leadership 

HPC and scientific computing and simulation are now firmly established as the third pillar of 
modern  research,  alongside  theory  and  experimentation115.  Thanks  to  steadily  increasing 
computing  power  with  the  introduction  of  massively  parallel  computer  systems  and 
widespread availability of HPC infrastructure (in particular since the 1990s), HPC has quickly 
become an essential component in nearly every field of scientific research.  

PRACE  is  the  only  pan-European  scheme  allocating  high-end  computational  resources  to 
scientific computational projects with a common scientific and technical peer-review based on 
excellence. The allocation of projects and resources awarded in the PRACE scheme can give 
a  good  indication  of  the  current  areas  with  bigger  demands  for  high-end  computing 
resources33: 

Figure 18 - Resources awarded in PRACE per area 

Areas 

Resources 
awarded 

Projects 
awarded 

Chemical Sciences and Materials 

Fundamental Constituents of Matter 

Engineering 

Universe Sciences 

Biochemistry, Bioinformatics and Life sciences 

Earth System Sciences 

Mathematics and Computer Sciences 

24% 

21% 

18% 

15% 

13% 

7% 

2% 

26% 

15% 

18% 

15% 

15% 

7% 

3% 

Today, many of the recent breakthroughs simply would not be possible without HPC. 

“The exponentially increasing advances of scientific computing can easily be 
taken  for  granted,  but  these  accomplishments  have  only  been  realised 
because  of  substantial,  and  ongoing, 
in  research  and 
infrastructure…  The  reason  for  these  advances  is  that  science  has  become 
interwoven with computing over the last half-century… What these advances 

investments 

74 

 
 
 
 
have  in  common  is  that  at  one  point  they  were  all  considered  absurdly 
difficult and far beyond the capabilities of mathematics, models and available 
computers  –  but  they  became  possible  to  solve  when  a  large  number  of 
individuals  invested  decades  of  effort  into  using  computing  to  model 
problems more difficult than anybody had imagined before.” 116 

Access  to  a  leading-class  HPC  infrastructure  with  the  most  advanced  supercomputers  is 
essential to address major scientific challenges that we face today. The use of supercomputers 
has  been  instrumental  in  the  Nobel  Prizes  of  Chemistry  in  2013  for  the  development  of 
multiscale  models  for  complex chemical systems,  and  of  Physics  in  2017  awarded  for  the 
discovery of gravitational waves.  

“A  world  class  European  computational  infrastructure  will  expand  the 
Frontiers  of  Fundamental  Sciences,  extending  and  complementing 
experiments.  ….  This  fundamental  research  advances  the  state-of-the-art  of 
scientific  computing  and  helps  attract  new  generations 
to  science, 
technology, engineering and mathematics.”  

The  applications  of  HPC  in  science  are  countless.  For  example,  in  fundamental  physics, 
advancing  the  frontiers  of  knowledge  of  matter  in  CERN  experiments,  or  exploring  the 
universe with data from advanced telescopes such as Hubble or the Square Kilometre Array; 
in  material  sciences,  for  the  design  of  new  components  critical  for  the  pharmaceutical  or 
energy sectors among many other fields; in fluid dynamics and adaptive control problems for 
the design of airplanes or planning of smart cities; in recognition of natural spoken language; 
in modelling the atmospheric and oceanic phenomena at planetary level, etc.  

It  is  probably  in  the  field  of  life  sciences  and  medicine  where  the  tremendous  impact  of 
bioinformatics is already very visible, for example in understanding generation and evolution 
of diseases (in particular cancer) and their early detection and treatment. This is made possible 
to the fast identification of genetic disease variants by supercomputers, processing billions of 
DNA sequences. HPC is also critical for simulating the human brain to study their structure, 
from  the  re-  or  de-generation  of  neurons  to  much  more  complex  cerebral  structures  and 
functions,  leading  for  example  to  valuable  insights  for  prevention  and  cure  of  Alzheimer’s 
disease. 

Societal challenges, policy making and national security 

Societal Challenges and policy making 

Citizens expect sustained improvements in their everyday life, while at the same time society 
is confronted with an increasing number of complex challenges – at the local urban and rural 
level  as  well  as  at  the  planetary  scale.  HPC  is  an  essential  tool  for  transforming  those 
challenges  into  innovation  and  bringing  opportunities  for  growth  and  jobs  that  the  EU 
economy needs.  

HPC  is  a  strategic  resource  for  policy-making,  helping  us  to  understand  our  ever-changing 
world, and providing a much-needed evidence for designing efficient solutions in many of the 
global  challenges.  Given  the  inter-disciplinary  nature  of  HPC  and  the  wide  range  of 
applications, citizens and policy makers will benefit from an increased level of computational 
resources in areas such as: 

  Weather  and  Climate  change:  HPC  underpins  climate  study  and  prediction  (weather 

forecast, catastrophes prevention and civil protection planning, etc.). 

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  Health,  demographic  change  and  wellbeing:  the  development  of  new  therapies  will 
heavily rely on HPC for understanding the nature of disease, discovering new drugs, and 
customising therapies to the specific needs of a patient 

  Secure, clean and efficient energy: HPC is a critical tool in developing fusion energy, in 
designing  high  performance  photovoltaic  materials  or  optimising  turbines  for  electricity 
production.  

  Smart, green and integrated urban planning: the control of large transport infrastructure 
in  smart  cities  will  require  the  real  time  analysis  of  huge  amounts  of  data  in  order  to 
provide  multivariable  decision/data  analytics  support  in  your  mobile  or  car.  In  addition, 
HPC can be used for monitoring of water and air quality, pollution control, etc. 

  Food  security,  sustainable  agriculture,  marine  research  and  the  bio-economy:  HPC  is 
used to optimise the production of food and analyse sustainability factors (e.g. plagues and 
diseases control, etc.). 

  Crisis management: In the last few  years, a huge number of people have been forced to 
leave their homes. One of the major issues is to forecast refugee movements, which would 
allow decision makers and NGOs to allocate humanitarian resources accordingly. An HPC 
simulation framework can help to accurately predict massive refugee movements coming 
from various conflict regions of the world. 

The  “Impact  Assessment  Study  for  Institutionalised  European  Partnerships  under  Horizon 
Europe  -  Candidate  Institutionalised  European  Partnership  in  High-Performance  Computing 
(Final  Report)”30  has  identified  eight  (of  17)  Sustainable  Development  Goals  (SDG)  where 
next-generation  HPC  systems  ought  to  make  a  meaningful  contribution,  alongside  an 
informed judgement as to the extent of the potential contribution to each SDG. Some of these 
impacts  could  materialise  via  HPC  contribution  to  Earth-observation  services,  weather 
forecasting,  ocean  forecast  and  climate  services,  disaster  prevention  and  crisis  management 
systems  such  as  those  from  Copernicus  (e.g.  Copernicus  emergency  monitoring  service, 
Copernicus  Climate  change  service,  Copernicus  marine  environmental  monitoring  service, 
and  others).  Furthermore,  HPC  can  also  lead  to  increased  rapid  response  capabilities.  For 
example,  EuroHPC  is  already  discussing  special  access  criteria  for  emergency  access  to 
EuroHPC  machines,  to  deal  with  disaster  situations  requiring  computing  power  at  a  short 
notice (floods, earthquakes, pollution, disease propagation, etc.)117. 

Figure 18 – Areas of contribution of HPC to Sustainable Development Goals 

SDG 

Extent of the contribution 

SDG 2 End hunger 

Via applications of HPC (medium) 

SDG3 Good Health and Well-being 

Via applications of HPC (high) 

SDG4 Quality Education 

Societal-level (medium) 

SDG7 Affordable and Clean Energy 

Via applications of HPC (high) 

SDG8 Decent Work and Economic Growth 

Direct contribution (high) 

SDG9 Industry, Innovation, and Infrastructure  Direct contribution (high) 

SDG13 Climate Action 

Via applications of HPC (high) 

SDG16 Peace, Justice, and Strong Institutions 

Via applications of HPC (medium) 

76 

 
 
 
EuroHPC  supports  world  leading  efforts  in  HPC  powered  simulations  and  applications  of 
direct  relevance  to  the  goals  of  a  European  Green  Deal,  notably  through  HPC  Centres  of 
Excellence.  These  Centres  focus  on  critical  challenges  such  as  Weather  and  Climate 
(ESiWACE)118,  Energy 
(CompBioMed2)120 , 
Biomolecular  research  (BioExcel-2)121,  Materials  (MaX)122,  Solid  Earth  geophysical 
monitoring (ChEESE)123, or complex Global Challenges (HiDALGO).124 

(EoCoE-2)119,  Biomedical  Applications 

One of the most striking examples of the use of HPC for societal challenges is weather and 
climate change, where exascale performance is absolutely needed to predict the size and paths 
of  storms  and  floods  earlier  and  more  accurately,  saving  lives  and  reducing  the  economic 
impact of the increasing damaging effects of climate change: 

The last twenty years have seen dramatic losses of human lives and economic 
output from climate-related disasters worldwide. According to the UN Office 
for  Disaster  Risk  Reduction125,  climate-related  and  geophysical  disasters 
were responsible for 1.3 million deaths between 1998 and 2017, and a further 
4.4 billion injured, homeless, displaced or in  need of  emergency assistance. 
91% of all disasters were caused by floods, storms, droughts, heatwaves and 
other extreme weather events.  

National security 

HPC  is  also  essential  for  national  security,  defence  and  national  sovereignty.  HPC  is 
recognised as a national strategic priority in the most powerful nations. Supercomputers are in 
the  first  line  for  nuclear  simulation  and  modelling,  cyber-criminality  and  cyber-security,  in 
particular  for  the  protection  of  critical  infrastructures.  HPC  is  also  increasingly  used  in  the 
fight against terrorism and crime, for example for face recognition or for suspicious behaviour 
in cluttered public spaces.  

“Leadership  in  high  performance  computing  remains  indispensable  to  a 
country's  industrial  competitiveness,  national  security,  and  potential  for 
scientific  discovery…  Advanced,  high  performance  computing  increasingly 
determines a nation's economic as well as defence security.”126 

“During the past five years, political leaders in the U.S., Europe, and China 
have  recognized  the  ability  of  leadership-class  supercomputers  to  help 
transform  their  economies,  their  societies,  and  their  understanding  of  the 
natural  world.  In  Japan  and  other  developed  countries,  leadership-class 
supercomputers  have  played  a  major  role  in  advancing  science,  boosting 
industrial competitiveness, and improving the quality of daily life for average 
citizens.”127 

HPC  is  a  new  weapon  in  cyber-war.  The  US  has  put  HPC  at  the  heart  of  cybersecurity 
practices in the public domain,128 identifying and analysing abundant opportunities for HPC 
use  and  elaborating  concepts,  planning  and  a  roadmap  toward  HPC-based  cybersecurity  to 
alleviate the cybersecurity dilemma on a national scale.  

Security  Roundup:  Ukraine  blocked  a  Russian  hack  of 
its  critical 
infrastructure:    Ukrainian  security  services  this  week  (July  2018)  said  they 
stopped  an  attempted  cyberattack  against  a  chlorine  distribution  plant. 
Russia has repeatedly targeted Ukraine, including devastating attacks on its 
power  grid.  In  this  case,  Russian  hackers  apparently  used  VPN  Filter 
malware-the same that infected half a million routers in May-to try to disrupt 

77 

 
 
the  operations  at  the  plant,  which  provides  clean  water  throughout  the 
country. Ukraine didn't offer many details about how exactly it thwarted the 
attack, but did say it headed off "possible catastrophic consequences."129 

"…  national  security  requires  the  best  computing  available,  and  loss  of 
leadership  in  HPC  will  severely  compromise  our  national  security  … 
National  Security  modelling  and  simulation  using  HPC  play  a  vital  role  in 
the design, development, and analysis of many – perhaps almost all – modern 
weapons systems and national security systems …. Simply put, leading-edge 
HPC  is  now  instrumental  to  getting  a  world-class,  large-scale  engineering 
system out the door …”107 

The exponential rise of the economic losses associated to cybercrime reveals also the need for 
secure and efficient infrastructures and for technologies that can anticipate and promptly react 
to an ever increasing menace:  

Every  day,  the  AV-TEST  Institute  registers  over  350,000  new  malicious 
programs  (~83.4%  malware  and  16.6%  potentially  unwanted  applications 
PUA in 2018). 130 

“Four  years  ago  in  2015,  the  global  cost  of  malware  was  an  already-
staggering EUR 450 billion. In just a short time, however, the economic toll 
of  cybercrime  has  grown  fourfold,  to EUR  1.8  trillion.  At  the  current 
trajectory, the total cost will reach EUR 5.4 trillion by 2021…. January 2019 
saw  the  release  of  nearly  two  billion  hacked  records  (that)  included  data 
from 202 million Chinese citizens and a database of FBI investigations… In 
2018, the cost of a data breach increased by 6.4% to EUR 3.5 million. In the 
US  only  it’s  more  like  EUR  7.12  million…  (in  2019)  organizations  and 
individuals  will  pay  EUR  10.35  billion,  either  as  a  cost  of  remediating 
ransomware  damage  or  simply  as  a  cost  of  paying  a  ransom….  Crypto-
jacking  malware  steals  your  CPU  cycles  to  mine  cryptocurrency,  and  it’s 
some  of  the  fastest-growing  malware  out  there,  with 8  million  attempts  per 
month at the beginning of 2018….”131, 132 

HPC and the COVID-19 crisis  

The use of HPC resources with big data sets, deep learning methods and large-scale complex 
computational  models  is  also  critical  to  effectively  support  policymakers  during  epidemic 
emergencies,  by  rapidly  forecasting  the  trajectory  of  the  spread  of  an  infectious  disease, 
planning  the  public  health  policy  response,  as  well  as  simulating  the  efficiency  of  different 
containment measures and evaluating the different post-epidemic scenarios.  

The  Commission  works  in  close  collaboration  with  the  PRACE  members  to  mobilise 
additional  supercomputing  resources  in  an  urgent/priority  access  scheme  for  computational 
research  targeting  COVID-19,  with  a  specific  call133  to  provide  researchers  with  access  to 
supercomputing resources for their coronavirus related activities. 

The European supercomputers are boosting their efforts in search for coronavirus treatment. 
The  EU-funded  supercomputing  project  “Exscalate4CoV”99  exploits  high-performance  HPC 
and  artificial  intelligence  (AI)  technologies  that  complement  traditional  biology  methods  to 
find  a  treatment  for  the  novel  coronavirus  disease,  with  support  from  supercomputers, 
biological institutes, research centres and pharmaceutical companies. 

78 

 
 
Led  by  Dompé,  a  pharmaceutical  company  based  in  Italy,  the  project  brings  together  three 
powerful  supercomputing  centres  –  CINECA  in  Italy,  BSC  in  Spain  and  JSC  in  Germany, 
several large biochemical institutes and research centres from seven European countries. E4C 
will receive €3 million of EU funding over 18 months. 

The  project  aims  to  identify  a  possible  treatment  for  Covid-19  patients.  They  use  a  "drug 
library" containing 500 billion molecules, matching them against the digitised proteins of the 
virus to  discover which combination of molecules would inhibit the virus. These operations 
have  already  given  promising  results,  with  over  50  potential  antiviral  molecules  identified 
from  the  computer  simulations  so  far.  Biologists  and  biochemists  are  now  working  on  the 
biological screening of these identified molecules.  

After this phase, the selected molecules will go through clinical testing to identify a possible 
treatment  for  patients.  The  project  has  already  started  discussions  with  the  European 
Medicines Agency on the regulatory process that will be required when moving to the clinical 
testing. 

The  success  of  E4C  also  depends  on  the  number  of  active  molecules  for  the  matching 
operations. In order to enlarge its “drug library”, the project, with the support of the European 
Federation  of  Pharmaceutical  Industries  and  Associations134,  launched  an  open  call  for 
collaboration with European pharmaceutical industries.  
Other  initiatives  such  as  the  CompBioMed  Centre  of  Excellence120  are  using  world  HPC 
resources to work on the following issues135: 

 

identifying  new  antiviral  drugs  by  screening  libraries  of  potential  drugs,  including 
those that have already been licensed to treat other diseases 

  accelerating vaccine development by identifying virus proteins or parts of protein that 

stimulate immunity 

  studying the spread of the virus within communities 

  analysing the origin and structure of the SARS-CoV-2 genome 

  studying  how  the  SARS-CoV-2  virus  interacts  with  human  cells  to  turn  them  into 

virus factories 

International efforts 

Other countries are also putting substantial HPC resources to tackle the COVID-19 crisis. Just 
a few examples are: 

  The US  has set  up the “COVID-19  High Performance Computing  Consortium”136, a 
public  private  partnership  with  the  Federal  government,  industry,  and  academic 
leaders coming together to provide access to high-performance computing resources in 
support  of  COVID-19  research.  This  complements  the  US  National  Science 
Foundation (NSF) to provisioning advanced cyberinfrastructure to further research on 
COVID-19137. 
 China’s  supercomputer  Tianhe-1138  has  been  dedicated  to  fight  COVID-19, 
specialising in training AI models to analyse hundreds of chest scans from patients in 
a few seconds and distinguishing between cases of pneumonic patients with COVID-
19 and patients with non-COVID-19 pneumonia, dramatically outperforming early test 
kits as well as human radiologists with nearly 80% accuracy. 

 

79 

 
 
  The  most  powerful  supercomputer  in  the  world,  the  Japanese  Fugaku139,  is  also 
helping  combat  the  COVID-19  pandemic,  by  giving  priority  to  research  selected  by 
the Japanese Ministry of Education, Culture, Sports, Science and Technology. 

  The  Joint  Supercomputer  Centre  of  the  Russian  Academy  of  Sciences  (RAS)140,  is 
working  to  develop  drugs  to  fight  against  COVID-19  with  massive  molecular 
dynamics  and  quantum  chemistry  simulations,  in  particular  by  studying  the  virus 
“spike” protein and its interactions with the human protein ACE2, which serves as the 
entry point for SARS-class viruses.  

  The  National  Supercomputing  Centre  (NSCC)141  in  Singapore  has  offered  its 
resources  to  Singapore  scientists  to  study  COVID-19,  issuing  a  fast-track  call  for 
projects to use the ASPIRE 1 petascale supercomputer.  

80 

 
 
 
Endnotes and web references 

1    Communication "A European Strategy for data" - COM(2020) 66 final 
2    Communication “Shaping Europe’s Digital Future” – COM(2020) 67 final 
3    Communication “Europe's moment: Repair and Prepare for the Next Generation” – COM(2020) 456 final - 
4  SWD(2018)  6  final  -  Impact  assessment  accompanying  the  “Proposal  for  a  Council  Regulation  on 

establishing the EuroHPC Joint Undertaking", Annex 5, 2017  

5    Communication “A European strategy for data” COM(2020) 66 final, https://ec.europa.eu/digital-single-

market/en/destination-earth-destine 

6    Council Regulation establishing the Joint Undertaking on High Performance Computing (EU) 2018/1488 of 

28 September 2018, OJ L252/1-34, 08.10.2018 

7    White paper on Artificial Intelligence - A European approach to excellence and trust – COM(2020) 65 final - 
8   PRACE (Partnership for Advanced Computing in Europe) www.prace-ri.eu  
9  GEANT, the pan-European high-speed network for scientific excellence, research, education and innovation 

www.geant.org  

10    https://ec.europa.eu/digital-single-market/en/quantum-technologies  
11    Horizon 2020 https://ec.europa.eu/programmes/horizon2020/en 
12    Connecting Europe Facility (CEF) https://ec.europa.eu/inea/en/connecting-europe-facility 
13    Communication "High-Performance Computing: Europe's place in a global race" - COM(2012) 45 final -  
14    Communication  "European  Cloud  Initiative  –  Building  a  competitive  data  and  knowledge  economy  in 

Europe" COM(2016) 178 final. 

15    Communication on the Mid-Term Review of the Digital Single Market Strategy - COM(2017) 228 final. 
16    Competitiveness Council adopting conclusions on the HPC Communication on 24 May 2013, Doc. 9808/13.  
17    Competitiveness Council conclusions on the ECI Communication on 29-30 May 2016, doc 9357/16. 
18    Conclusions of the European Council of 28 June 2016.  
19   European  Parliament,  Report  on  the  European  Cloud  Initiative  (2016/2145(INI)),  ITRE  Committee,  26 

January 2017. 

20   Council conclusions on shaping Europe's digital future, 09 June 2020, doc 8711/20. 
21  7th 

Programme 

Framework 

European 

Research 

and 

for 

Innovation 

(FP7) 

https://ec.europa.eu/research/fp7/index_en.cfm 

22    European Technology Platform (ETP4HPC) Association http://www.etp4hpc.eu/ 
23    Big Data Value Association http://www.bdva.eu/  
24   Digital  Single  Market:  Europe  announces  eight  sites  to  host  world-class  supercomputers,  7  June  2019 

http://europa.eu/rapid/press-release_IP-19-2868_en.htm 

25  EuroHPC  Call 

for 

proposals 

for  R&I 

actions 

2019, 

https://ec.europa.eu/digital-single-

market/en/news/eurohpc-joint-undertaking-launches-first-research-and-innovation-calls 

26   European  Processor  Initiative  Framework  Partnership  Agreement  (FPA)  https://www.european-processor-

initiative.eu/ 

27  Topic 

INFRAEDI-05-2020: 

exascale 
https://ec.europa.eu/research/participants/data/ref/h2020/wp/2018-2020/main/h2020-wp1820-
infrastructures_en.pdf 

Excellence 

Centres 

of 

in 

computing 

28   https://ec.europa.eu/research/participants/data/ref/h2020/wp/2018-2020/main/h2020-wp1820-fet_en.pdf 
29   “Financing the future of supercomputing: How to increase the investments in high performance computing in 

Europe”, EIB 2017,  https://www.eib.org/en/publications/financing-the-future-of-supercomputing 

30   “Forthcoming external Study : “Impact Assessment Study for Institutionalised European Partnerships under 
Horizon Europe  - Candidate  Institutionalised European Partnership in High-Performance  Computing (Final 
Report)”, Technopolis (2020), supported by DG RTD  

81 

 
 
                                                 
31   Top world supercomputers, https://www.top500.org/  
32   ASCR facilities available at https://science.energy.gov/user-facilities/user-facilities-at-a-glance/ascr/  
33   PRACE resources http://www.prace-ri.eu/prace-resources/ 
34   PRACE KPIs at: http://www.prace-ri.eu/prace-kpi/ 
35  Horizon 

Annotated 

Grant 

2020, 

agreement, 

https://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/amga/h2020-amga_en.pdf 

36   https://ec.europa.eu/digital-single-market/en/digital-innovation-hubs 
37  Fortissimo 
booklet 

Fortissimo 

and 

2 

- 

https://www.fortissimo-

project.eu/sites/default/files/Fortissimo_SS_Booklet_web_0.pdf 

38   EXDCI project, https://exdci.eu/ 
39   Exanode project, http://exanode.eu/ 
40   Exanest project, https://www.exanest.eu/ 
41   Euroexa project, https://euroexa.eu/ 
42   Mango project, https://cordis.europa.eu/project/id/671668 
43   Montblanc projects, https://www.montblanc-project.eu/ 
44   SME HPC Adoption Programme in Europe, https://prace-ri.eu/prace-for-industry/shape-access-for-smes/ 
45   “The EuroHPC mission and strategy for the next decade”, EuroHPC JU Industrial and Scientific Advisory 

Board, internal document for the EuroHPC JU Governing Board 

46   European “1+ Million Genomes” initiative launched in 2018, https://ec.europa.eu/digital-single-

market/en/european-1-million-genomes-initiative 

47   US President Trump, Executive order on maintaining American leadership in AI, February 2019 

https://www.whitehouse.gov/presidential-actions/executive-order-maintaining-american-leadership-artificial-
intelligence/ 

48   Enterprise Europe Network https://een.ec.europa.eu/ 
49   OpenAI  analysis  2019,  https://www.technologyreview.com/s/614700/the-computing-power-needed-to-train-

ai-is-now-rising-seven-times-faster-than-ever-before/  

50  World 

Economic 

Forum, 

“How 

much 

data 

is 

generated 

each 

day? 

https://www.weforum.org/agenda/2019/04/how-much-data-is-generated-each-day-cf4bddf29f/ 

51   Square Kilometre Array (SKA), https://www.skatelescope.org/the-ska-project/ 
52   ESA  "https://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Copernicus_20_years_on"  
53   Genomic data  challenges of the  future, the Medical Futurist 2018,  https://medicalfuturist.com/the-genomic-

data-challenges-of-the-future/ 

54   CERN computational and storage needs https://home.cern/science/computing/storage 
55   Science Direct, Moore’s law https://www.sciencedirect.com/topics/computer-science/moores-law 
56  Cray  Wins  NNSA-Livermore 

‘El  Capitan’  Exascale  Contract,  HPCWire,  13  August  2019 

https://www.hpcwire.com/2019/08/13/cray-wins-nnsa-livermore-el-capitan-exascale-award/ 

57   https://ec.europa.eu/newsroom/dae/document.cfm?doc_id=65402 
58   https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM%3A2018%3A434%3AFIN  
59   Commission Staff Working Document – Impact Assessment accompanying the Proposal for a Regulation of 
the European Parliament and of the Council establishing the Digital Europe programme for the period 2021-
2027 {COM(2018) 434 final} - {SEC(2018) 289 final} - {SWD(2018) 306 final} 

60   A  Union  that  strives  for  more,  European  Commission  2019,  https://ec.europa.eu/commission/sites/beta-

political/files/political-guidelines-next-commission_en.pdf 

61   Communication “European Green Deal” - COM (2019) 640 final 
62   https://ec.europa.eu/info/sites/info/files/communication-shaping-europes-digital-future-feb2020_en_4.pdf 
63   Communication “A New Industrial Strategy for Europe” - COM(2020) 102 final. 
64   Communication “An SME Strategy for a sustainable and digital Europe” - COM(2020) 103 final. 

82 

 
 
                                                                                                                                                         
65    Staff Working Document “Identifying Europe's recovery needs” - SWD(2020) 98 final - 
66    Communication “The EU budget powering the recovery plan for Europe” – COM(2020) 442 final - 
67  Horizon  Europe  (HE)  -  COM/2018/436  final  -  2018/0225  (COD)  -  https://eur-lex.europa.eu/legal-

content/EN/TXT/?uri=COM%3A2018%3A436%3AFIN 

68   Connecting  Europe  Facility  (CEF-2)  -  COM/2018/438  final  -  https://ec.europa.eu/commission/sites/beta-

political/files/budget-may2018-cef-regulation_en.pdf 

69   PRACE training events https://events.prace-ri.eu/category/1/ 
70   SesameNet https://sesamenet.eu/  
71   ECSEL Joint Undertaking for Electronic Components and Systems https://www.ecsel.eu/ 
72   EOSC https://ec.europa.eu/research/openscience/index.cfm?pg=open-science-cloud 
73   EOSC portal: https://www.eosc-portal.eu/  
74   IDC Spending Forecast, 2018 https://www.idc.com/promo/global-ict-spending/forecast 
75   Creating  Economic  Models  Showing  the  Relationship  Between  Investments  in  HPC  and  the  Resulting 
Financial  ROI and Innovation  — and How It Can Impact a Nation's Competitiveness and Innovation, IDC 
2013, https://www.hpcuserforum.com/ROI/ 

76   Study  SMART  2014/0021  for  the  EC  "High-Performance  Computing  in  the  EU:  Progress  on  the 
Implementation  of  the  European  HPC  Strategy";  IDC  2015.  https://publications.europa.eu/en/publication-
detail/-/publication/5a7cfd63-d59a-4211-8b28-0c72cad7068c/language-en 

77   Economic Models Linking HPC and ROI, Hyperion 2018, https://www.hpcuserforum.com/ROI/ 
78   HPC 

for  Government,  Academia 
https://www.hpcuserforum.com/presentations/Wisconsin2017/HyperionUSHPCOpportunitesforEngagement.
pdf 

engagement  opportunities 

Industry,  Hyperion  2017 

and 

79   Eurostat 2018, https://ec.europa.eu/growth/index_en 
80   Eurostat  2018  https://ec.europa.eu/growth/index_en,  DG  GROW  https://ec.europa.eu/growth/index_en, 
and 

https://www.efpia.eu/media/361960/efpia-pharmafigures2018_v07-hq.pdf, 

EFPIA 
https://en.wikipedia.org/wiki/List_of_largest_oil_and_gas_companies_by_revenue  

81  How  HPC 

is  Helping 

2017, 
https://www.cloud28plus.com/emea/content/https---verneglobal-com-blog-how-hpc-is-helping-the-future-of-
weather-prediction 
82  Extreme  weather 

of  Weather  Prediction,  Weather  Analytics 

the  Future 

increase 

century' 

50-fold 

Europe 

deaths 

'could 

next 

by 

in 

https://www.theguardian.com/science/2017/aug/04/extreme-weather-deaths-in-europe-could-increase-50-
fold-by-next-century 

83  The 

Economic 

Consequences 

of 

Climate 

Change,  OECD 

2015, 

https://www.oecd-

ilibrary.org/environment/the-economic-consequences-of-climate-change_9789264235410-en 

84   List of sources: 
  Hyperion 

Research 

Update 

2019 

(November): 

https://hyperionresearch.com/wp-

content/uploads/2019/06/Hyperion-Research-ISC19-Breakfast-Briefing-Presentation-June-2019.pdf and  
https://www.hpcwire.com/2019/11/21/hyperion-ai-driven-hpc-industry-continues-to-push-growth-
projections/ 

  Hyperion 

2019 
content/uploads/2019/06/Hyperion-Research-ISC19-Breakfast-Briefing-Presentation-June-2019.pdf,  

https://hyperionresearch.com/wp-

Research 

Update 

– 

  Worldwide  Public  Cloud  Services  Spending  Forecast 
https://www.idc.com/getdoc.jsp?containerId=prUS44891519, 
https://insidehpc.com/2019/06/hpc-market-five-year-forecast-bumps-up-to-44-billion-worldwide/ 

to  Reach  $210  Billion  This  Year, 
update 

Hyperion 

2019 

  HYPERION  RESEARCH  UPDATE:  Research  Highlights  In  HPC,  HPDA-AI,  Cloud  Computing, 
Quantum  Computing,  and  Innovation  Award  Winners,  2019,  https://hyperionresearch.com/wp-
content/uploads/2019/06/Hyperion-Research-ISC19-Breakfast-Briefing-Presentation-June-2019.pdf 

85   WCCTech  2019,  AMD  and  the  market  2019,  https://wccftech.com/amd-cpu-market-share-highest-since-

2013-ryzen-threadripper-epyc/  

83 

 
 
                                                                                                                                                         
86   https://venturebeat.com/2019/12/11/risc-v-grows-globally-as-an-alternative-to-arm-and-its-license-fees/ 
87   https://technode.com/2019/07/24/chinas-chipmakers-risc-v-sanctions/ 
88  RAND,https://www.rand.org/content/dam/rand/pubs/research_reports/RR1400/RR1478/RAND_RR1478.pdf 
89   GAIA-X,  Dotmagazine  2019,  https://www.dotmagazine.online/issues/on-the-edge-building-the-foundations-

for-the-future/gaia-x-a-vibrant-european-ecosystem 

90  Worldwide 

Public 

Cloud 

Services 

Spending 

Forecast, 

IDC 

2019, 

 https://www.idc.com/getdoc.jsp?containerId=prUS44891519 

91  HPCwire  October  2019,  https://www.hpcwire.com/solution_content/ibm/cross-industry/spooky-hpc-cloud-

computing-stats-just-in-time-for-halloween/ 

92   Arm A64fx and Post-K: Game Changing CPU & Supercomputer for HPC and its Convergence of with Big 
2019, 

AI, 
Data 
https://www.hpcuserforum.com/presentations/april2019/Rikenmatsuoka.pdf 
93    Communication "Artificial intelligence for Europe"- COM(2018) 237 final 
94    What is Industry 4.0?, Forbes 2018, https://www.forbes.com/sites/bernardmarr/2018/09/02/what-is-industry-

Matsuoka 

Satoshi 

/ 

4-0-heres-a-super-easy-explanation-for-anyone/ 

95    Artificial  Intelligence  and  the  future  of  Defence,  The  Hague  Centre  for  Strategic  Studies  2017, 
https://hcss.nl/sites/default/files/files/reports/Artificial%20Intelligence%20and%20the%20Future%20of%20
Defense.pdf 

96   US 

President  Trump 

budget 

request 

for 

2020, 

2019, 

https://www.whitehouse.gov/wp-

content/uploads/2019/03/budget-fy2020.pdf 

97    Gartner  Top 

6 

Security 

and  Risk  Management  Trends 

for 

2018,  Gartner 

2018, 

https://www.gartner.com/smarterwithgartner/gartner-top-5-security-and-risk-management-trends/ 

98    ANTAREX project,  http://www.antarex-project.eu/ and https://www.exscalate.eu/ 
99   Exscalate4CoV project, https://www.exscalate4cov.eu/ 
100   Human Brain project (HBP), https://www.humanbrainproject.eu/en/  
101   Pl@ntnet, https://identify.plantnet.org/   
102   CALIOPE 
project, 

http://www.bsc.es/caliope/es/ 

and 

http://www.aire.cdmx.gob.mx/pronostico-

aire/index.php 

103  IoTwins, http://www.hpc.cineca.it/news/iotwins-project-digital-twins-industrial-plants 
104  CERN, 

in  CERN: 

of  AI 

and 

use 

the 

: 

https://www.hpcwire.com/2018/08/14/cern-incorporates-ai-into-physics-based-simulations/, 
chips.nl/artikel/cern-uses-vub-ai-methods-to-decode-the-universe/ 

https://home.cern/science/computing/storage, 
https://bits-

105  https://www.cray.com/sites/default/files/Tractica-White-Paper_Use-Cases-for-AI-in-HPC.pdf 
106  Digital Single Market, Digitising the European industry  
107  U.S. Leadership in High Performance Computing (HPC) - A Report from the NSA-DOE Technical Meeting 
2016, 

on 
December 
https://www.nitrd.gov/nitrdgroups/images/b/b4/NSA_DOE_HPC_TechMeetingReport.pdf  

Performance 

Computing, 

High 

108   PRACE Industry Access -  http://www.prace-ri.eu/prace-supports-industry/ 
109  Excellerat Centre of Excellence,  https://www.excellerat.eu/ 
110  POP2 Centre of Excellence, https://pop-coe.eu/ 
111   The cloud enables next generation digital twin, Microsoft, 2018, https://cloudblogs.microsoft.com/industry-

blog/manufacturing/2018/08/20/the-cloud-enables-next-generation-digital-twin/ 

112  Digital  twins,  Deloitte  2020  https://www2.deloitte.com/us/en/insights/focus/tech-trends/2020/digital-twin-

applications-bridging-the-physical-and-digital.html 

113  Digital  Twin  Predictions:  The  Future  Is  Upon  Us,  PTC  2019,  https://www.ptc.com/en/product-lifecycle-

report/digital-twin-predictions 

114  IDC 

FutureScape: 

Worldwide 

IoT 

2018 

Predictions, 

IDC 

2017,  

https://www.idc.com/research/viewtoc.jsp?containerId=US43161517 

84 

 
 
                                                                                                                                                         
 
115  https://www.researchgate.net/publication/220405901_Research_advances_by_using_interoperable_e-

science_infrastructures  

116  The Scientific Case for Computing in Europe 2018 – 2026, PRACE 2018, https://www.eu-maths-in.eu/wp-

content/uploads/2018/05/MSO-vision.pdf 

117 Workshop on EuroHPC Systems Access Policy, 2019. Sergi Girona 2019: 

https://www.youtube.com/watch?v=DIQthdbBl_Y 

118  ESIWACE Centre of Excellence, https://www.esiwace.eu/ 
119  EoCoE Centre of Excellence, https://www.eocoe.eu/ 
120  CompBioMed Centre of Excellence,  https://www.compbiomed.eu/ 
121  BioExcel Centre of Excellence,  https://bioexcel.eu/ 
122  MaX - Materials design at the Exascale, http://www.max-centre.eu/ 
123  Cheese Centre of Excellence, https://cheese-coe.eu/ 
124  Hidalgo Centre of Excellence,  https://hidalgo-project.eu/ 
125  Economic 
disasters: 

poverty 

losses, 

& 

1998-2017, 

UNDRR 

report 

2018, 

https://www.unisdr.org/we/inform/publications/61119 

126  The  Vital 

Importance 

of  High-Performance  Computing 

to  U.S.  Competitiveness, 

ITIF, 

https://itif.org/publications/2016/04/28/vital-importance-high-performance-computing-us-competitiveness 
127  Investigation  of  the  Ripple  Effects  of  Developing  and  Utilizing  Leadership  Supercomputers  in  Japan, 
  https://www.r-ccs.riken.jp/r-ccssite/wp-content/uploads/2016/12/IDC-Study-for-Riken-Ripple-

Hyperion 
Effects_final.pdf 

128  National  Cyber  Defence  High  Performance  Computing  and  Analysis:  Concepts,  Planning  and  Roadmap  () 

https://prod-ng.sandia.gov/techlib-noauth/access-control.cgi/2010/104766.pdf) 

129  Wired,  2018,  https://www.wired.com/story/security-roundup-ukraine-blocked-a-russian-hack-of-its-critical-

infrastructure/ 

130  The Independent IT-Security Institute (AV-TEST), 2019,  https://www.av-test.org/en/statistics/malware/ 
131   Malware 

detectives 

Statistics, 

Trends 

Safety 

2019, 

Facts 

and 

in 

2019, 

https://www.safetydetectives.com/blog/malware-statistics/ 

132  21  Terrifying  Cyber  Crime  Statistics,  Data  Connectors  2018,    https://dataconnectors.com/technews/21-

terrifying-cyber-crime-statistics/ 

133  http://prace-ri.eu/prace-support-to-mitigate-impact-of-covid-19-pandemic/ 
134  EFPIA association, https://www.efpia.eu/  
135  https://sciencebusiness.net/network-updates/ucl-researchers-are-using-worlds-most-powerful-

supercomputers-tackle-covid-19 
136  https://covid19-hpc-consortium.org/ 
137  https://www.hpcwire.com/off-the-wire/nsf-provisioning-advanced-cyberinfrastructure-to-further-research-on-

covid-19/ 

138  https://www.scmp.com/news/china/society/article/3075153/coronavirus-chinese-supercomputer-uses-

artificial-intelligence 

139  https://www.riken.jp/en/news_pubs/news/2020/20200407_1/index.html 
140  https://www.hpcwire.com/2020/03/31/russian-supercomputer-employed-to-develop-covid-19-treatment/ 
141  https://www.hpcwire.com/off-the-wire/singapores-national-supercomputing-resources-joins-the-fight-

against-covid-19/ 

85