bluuebunny/crossref_metadata_2025 huggingface dataset:
Recent evolutions in the LTDP CDF project
Authors: Fornari Federico , Fattibene Enrico , Cavalli Alessandro , Cesini Daniele , Falabella Antonio , Morganti Lucia , Prosperini Andrea , Sapunenko Vladimir
Published: November 2020

In the latest years, CNAF (the national center of the Italian Institute for Nuclear Physics INFN dedicated to Research and Development on Information and Communication Technologies) has been working on the Long Term Data Preservation (LTDP) project for the CDF experiment, active at Fermilab from 1990 to 2011. The main aims of the project are to protect the most relevant part of the CDF RUN-2 data collected between 2001 and 2011 and already stored on tape at CNAF (4 PB), as well as to ensure the availability and the access to the analysis facility to those data over time. Lately, the CDF database, hosting information about CDF datasets such as their structure, file locations and metadata, has been imported from Fermilab to CNAF. Also, the Sequential Access via Metadata (SAM) station data handling tool for CDF data management, that allows to manage data transfers and to retrieve information from the CDF database, has been properly installed and configured at CNAF. This was a fundamental step in the perspective of a complete decommissioning of CDF services on Fermilab side. An access system has been designed and tested to submit CDF analysis jobs, using CDF software distributed via CERN Virtual Machine File System (CVMFS) and requesting delivery of CDF files stored on CNAF tapes, as well as data present only on Fermilab storage archive. Moreover, the availability and the correctness of all CDF data stored on CNAF tapes has been verified. This paper describes all these recent evolutions in detail, presenting the future plans for the LTDP project at CNAF.
The GridKa Tape Storage: various performance test results and current improvements
Authors: Musheghyan Haykuhi , Petzold Andreas , Heiss Andreas , Ressmann Doris , Beitzinger Martin
Published: November 2020

Data growth over several years within HEP experiments requires a wider use of storage systems for WLCG Tiered Centers. It also increases the complexity of storage systems, which includes the expansion of hardware components and thereby complicates existing software products more. To cope with such systems is a non-trivial task and requires highly qualified specialists. Storing petabytes of data on tape storage is a still the most cost-effective way. Year after year, the use of a tape storage increases, consequently a detailed study of its optimal use and verification of performance is a key aspect for such a system. It includes several factors, such as performing various performance tests, identifying and eliminating bottlenecks, properly adjusting and improving the current GridKa setup, etc.

At present, GridKa uses dCache as the storage system in frontend and TSM as the tape storage backend. dCache provides a plugin interface for exchanging data between dcache and tape.

TSS is a TSM-based client developed by the GridKa team. TSS has been in production for over 10 years. The interaction between the GridKa dCache instance and TSM is accomplished using additional scripts that can be further optimized to improve the overall performance of the tape storage.

This contribution provides detailed information on the results of various performance tests performed on the GridKa tape and significant improvements of our tape storage performance.
Fast distributed compilation and testing of large C++ projects
Authors: Matev Rosen
Published: November 2020

High energy physics experiments traditionally have large software codebases primarily written in C++ and the LHCb physics software stack is no exception. Compiling from scratch can easily take 5 hours or more for the full stack even on an 8-core VM. In a development workflow, incremental builds often do not significantly speed up compilation because even just a change of the modification time of a widely used header leads to many compiler and linker invokations. Using powerful shared servers is not practical as users have no control and maintenance is an issue. Even though support for building partial checkouts on top of published project versions exists, by far the most practical development workflow involves full project checkouts because of off-the-shelf tool support (git, intellisense, etc.)

This paper details a deployment of distcc, a distributed compilation server, on opportunistic resources such as development machines. The best performance operation mode is achieved when preprocessing remotely and profiting from the shared CernVM File System. A 10 (30) fold speedup of elapsed (real) time is achieved when compiling Gaudi, the base of the LHCb stack, when comparing local compilation on a 4 core VM to remote compilation on 80 cores, where the bottleneck becomes non-distributed work such as linking. Compilation results are cached locally using ccache, allowing for even faster rebuilding. A recent distributed memcached-based shared cache is tested as well as a more modern distributed system by Mozilla, sccache, backed by S3 storage. These allow for global sharing of compilation work, which can speed up both central CI builds and local development builds. Finally, we explore remote caching and execution services based on Bazel, and how they apply to Gaudi-based software for distributing not only compilation but also linking and even testing.
GPU Usage in ATLAS Reconstruction and Analysis
Authors: Krasznahorkay Attila , Leggett Charles , Mete Alaettin Serhan , Snyder Scott , Tsulaia Vakho
Published: November 2020

With Graphical Processing Units (GPUs) and other kinds of accelerators becoming ever more accessible, High Performance Computing Centres all around the world using them ever more, ATLAS has to find the best way of making use of such accelerators in much of its computing.

Tests with GPUs – mainly with CUDA – have been performed in the past in the experiment. At that time the conclusion was that it was not advantageous for the ATLAS offline and trigger software to invest time and money into GPUs. However as the usage of accelerators has become cheaper and simpler in recent years, their re-evaluation in ATLAS’s offline software is warranted.

We show new results of using GPU accelerated calculations in ATLAS’s offline software environment using the ATLAS offline/analysis (xAOD) Event Data Model. We compare the performance and flexibility of a couple of the available GPU programming methods, and show how different memory management setups affect our ability to offload different types of calculations to a GPU efficiently.
ART ATLAS Release Tester using the Grid
Authors: Cuhadar Donszelmann Tulay , Lampl Walter , Stewart Graeme A.
Published: November 2020

The ART (ATLAS Release Tester) system is designed to run test jobs on the Grid after a nightly release of the ATLAS offline software has been built. The choice was taken to exploit the Grid as a backend as it offers a huge resource pool, suitable for a deep set of integration tests, and running the tests could be delegated to the highly scalable ATLAS production system (PanDA). The challenge of enabling the Grid as a test environment is met through the use of the CVMFS file system for the software and input data files. Test jobs are submitted to the Grid by the GitLab Continuous Integration (gitlab-ci) system, which itself is triggered at end of a release build. Jobs can be adorned with special headers that inform the system how to run the specific test, allowing many options to be customised. The gitlab-ci system waits for exit status and output files are copied back from the Grid to an EOS area accessible by users. All gitlab-ci jobs run in ART’s virtual machines, using docker images for their ATLAS setup. ART jobs can be tracked by using the PanDA system. ART can also be used to run short test jobs locally. It uses the same ART command-line interface, where the backend is replaced to access a local machine for job submission rather than the Grid. This allows developers to ensure their tests work correctly before adding them to the system. In both the Grid and local machine options, running and result copying are completely parallelized. ART is written in python, complete with its own local and Grid tests to give approximately 90% code coverage of the ART tool itself. ART has been in production for one year and fully replaces and augments the former ATLAS testing system.
MarlinMT - parallelising the Marlin framework
Authors: Ete Remi , Gaede Frank , Benda Julian , Grasland Hadrian
Published: November 2020

Marlin is the event processing framework of the iLCSoft [1] ecosystem. Originally developed for the ILC more than 15 years ago, it is now widely used also by other communities, such as CLICdp, CEPC and many test beam projects such as CALICE, LCTPC and EU-Telescope. While Marlin is lightweight and flexible it was originally designed for sequential processing only. With MarlinMT we have now evolved Marlin for parallel processing of events on multi-core architectures based on multi-threading. We report on the necessary developments and issues encountered, within Marlin as well as with the underlying LCIO [4] event data model (EDM). A focus will be put on the new parallel event processing (PEP) scheduler. We conclude with first performance estimates, like the application speedup and a discussion on histogram handling in parallel applications.
Impact of different compilers and build types on Geant4 simulation execution time
Authors: Marcon Caterina , Smirnova Oxana , Muralidharan Servesh
Published: November 2020

Experimental observations and advanced computer simulations in High Energy Physics (HEP) paved the way for the recent discoveries at the Large Hadron Collider (LHC) at CERN. Currently, Monte Carlo simulations account for a very significant amount of computational resources of the Worldwide LHC Computing Grid (WLCG). The current growth in available computing performance will not be enough to fulfill the expected demand for the forthcoming High Luminosity run (HL-LHC). More efficient simulation codes are therefore required.

This study focuses on evaluating the impact of different build methods on the simulation execution time. The Geant4 toolkit, the standard simulation code for the LHC experiments, consists of a set of libraries which can be either dynamically or statically linked to the simulation executable. Dynamic libraries are currently the preferred build method.

In this work, three versions of the GCC compiler, namely 4.8.5, 6.2.0 and 8.2.0 have been used. In addition, a comparison between four optimization levels (Os, O1, O2 and O3) has also been performed.

Static builds for all the GCC versions considered, exhibit a reduction in execution times of about 10%. Switching to newer GCC version results in an average of 30% improvement in the execution time regardless of the build type. In particular, a static build with GCC 8.2.0 leads to an improvement of about 34% with respect to the default configuration (GCC 4.8.5, dynamic, O2). The different GCC optimization flags do not affect the execution times.
A New PyROOT: Modern, Interoperable and More Pythonic
Authors: Galli Massimiliano , Tejedor Enric , Wunsch Stefan
Published: November 2020

Python is nowadays one of the most widely-used languages for data science. Its rich ecosystem of libraries together with its simplicity and readability are behind its popularity. HEP is also embracing that trend, often using Python as an interface language to access C++ libraries for the sake of performance. PyROOT, the Python bindings of the ROOT software toolkit, plays a key role here, since it allows to automatically and dynamically invoke C++ code from Python without the generation of any static wrappers beforehand. In that sense, this paper presents the efforts to create a new PyROOT with three main qualities: modern, able to exploit the latest C++ features from Python; pythonic, providing Python syntax to use C++ classes; interoperable, able to interact with the most important libraries of the Python data science toolset.
Emergent Structure in QCD
Authors: Biddle James , Kamleh Waseem , Leinweber Derek
Published: November 2020

The structure of the S U(3) gauge-field vacuum is explored through visualisations of centre vortices and topological charge density. Stereoscopic visualisations highlight interesting features of the vortex vacuum, especially the frequency with which singular points appear and the important connection between branching points and topological charge. This work demonstrates how visualisations of the QCD ground-state fields can reveal new perspectives of centre-vortex structure.
Extreme Compression for Large Scale Data Store
Authors: Lauret Jérôme , Gonzalez Juan , Van Buren Gene , Nuñez Rafael , Canal Philippe , Naumann Axel
Published: November 2020

For the last 5 years Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom line outcome would be to provide a state-of-the-art compression algorithm that surpasses those currently available in the ROOT framework, with the purpose of enabling substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4.

In this contribution, we will present our concepts of “functionally lossless compression”, have a glance at examples and achievements in other communities, present the results and outcome of our current, ongoing R&D, as well as present a high-level view of our plan to move forward with a ROOT implementation that would deliver a basic solution readily integrated into HENP applications. As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility.
The Scikit HEP Project overview and prospects
Authors: Rodrigues Eduardo , Krikler Benjamin , Burr Chris , Smirnov Dmitri , Dembinski Hans , Schreiner Henry , Nandi Jaydeep , Pivarski Jim , Feickert Matthew , Marinangeli Matthieu , Smith Nick , Das Pratyush
Published: November 2020

Scikit-HEP is a community-driven and community-oriented project with the goal of providing an ecosystem for particle physics data analysis in Python. Scikit-HEP is a toolset of approximately twenty packages and a few “affiliated” packages. It expands the typical Python data analysis tools for particle physicists. Each package focuses on a particular topic, and interacts with other packages in the toolset, where appropriate. Most of the packages are easy to install in many environments; much work has been done this year to provide binary “wheels” on PyPI and conda-forge packages. The Scikit-HEP project has been gaining interest and momentum, by building a user and developer community engaging collaboration across experiments. Some of the packages are being used by other communities, including the astroparticle physics community. An overview of the overall project and toolset will be presented, as well as a vision for development and sustainability.
Evaluation of a new visualization and analytics solution for slow control data for large scale experiments
Authors: Sargsyan Laura , Martins Filipe
Published: November 2020

Large experiments in high energy physics require efficient and scalable monitoring solutions to digest data of the detector control system. Plotting multiple graphs in the slow control system and extracting historical data for long time periods are resource intensive tasks. The proposed solution leverages the new virtualization, data analytics and visualization technologies such as InfluxDB time-series database for faster access large scale data, Grafana to visualize time-series data and an OpenShift container platform to automate build, deployment, and management of application. The monitoring service runs separately from the control system thus reduces a workload on the control system computing resources. As an example, a test version of the new monitoring was applied to the ATLAS Tile Calorimeter using the CERN Cloud Process as a Service platform. Many dashboards in Grafana have been created to monitor and analyse behaviour of the High Voltage distribution system. They visualize not only values measured by the control system, but also run information and analytics data (difference, deviation, etc.). The new monitoring with a feature-rich visualization, filtering possibilities and analytics tools allows to extend detector control and monitoring capabilities and can help experts working on large scale experiments.
ComputeOps: Container for High Performance Computing
Authors: Cavet Cécile , Souchal Martin , Gadrat Sébastien , Grasseau Gilles , Satirana Andrea , Bailly-Reyre Aurélien , Dadoun Olivier , Mendoza Victor , Chamont David , Marchal-Duval Gérard , Medernach Emmanuel , Pansanel Jérôme
Published: November 2020

The High Performance Computing (HPC) domain aims to optimize code in order to use the latest multicore and parallel technologies including specific processor instructions. In this computing framework, portability and reproducibility are key concepts. A way to handle these requirements is to use Linux containers. These “light virtual machines” allow to encapsulate applications within its environment in Linux processes. Containers have been recently rediscovered due to their abilities to provide both multi-infrastructure environnement for developers and system administrators and reproducibility due to image building file. Two container solutions are emerging: Docker for microservices and Singularity for computing applications. We present here the status of the ComputeOps project which has the goal to study the benefit of containers for HPC applications.
Jupyter-based service for JUNO analysis
Authors: Lin Tao
Published: November 2020

The JUNO (Jiangmen Underground Neutrino Observatory) is designed to determine the neutrino mass hierarchy and precisely measure oscillation parameters. The estimated data volume of raw data is about 2 PB/year. The event rate of reactor anti-neutrinos is about 60/day, while the event rate of background is about O(10) Hz. The challenge is the event correlation during the analysis, where the background events could not be discarded. In order to use big data techniques to search for rare events, a Jupyter-based interactive service is developed for JUNO analysis.

In this paper, an overview of this service is presented. The infrastructure is based on Jupyter and Kubernetes, which provides the user interface and resource management. In order to integrate the data processing framework and big data techniques, an index file is used as an intermediate file, which points to the interested events. Data processing framework SNiPER is used to select the candidate of neutrino signals and produce the index file. Apache Spark is then used to process such index file repeatedly with data cached in memory. With the index file produced from Spark and the complete event data files, SNiPER is used to process them and produce the final physics result. At the end of paper, the test-bed is presented and the testing result is shown.
Effective Dynamic Integration and Utilization of Heterogenous Compute Resources
Authors: Fischer Max , Giffels Manuel , Heiss Andreas , Kuehn Eileen , Schnepf Matthias , von Cube Ralf Florian , Petzold Andreas , Quast Günter
Published: November 2020

Increased operational effectiveness and the dynamic integration of only temporarily available compute resources (opportunistic resources) becomes more and more important in the next decade, due to the scarcity of resources for future high energy physics experiments as well as the desired integration of cloud and high performance computing resources. This results in a more heterogenous compute environment, which gives rise to huge challenges for the computing operation teams of the experiments.

At the Karlsruhe Institute of Technology (KIT) we design solutions to tackle these challenges. In order to ensure an efficient utilization of opportunistic resources and unified access to the entire infrastructure, we developed the Transparent Adaptive Resource Dynamic Integration System (TARDIS). A scalable multi-agent resource manager providing interfaces to provision as well as dynamically and transparently integrate resources of various providers into one common overlay batch system. Operational effectiveness is guaranteed by relying on COBalD – the Opportunistic Balancing Daemon and its simple approach of taking into account the utilization and allocation of the different resource types, in order to run the individual workflows on the best-suited resource respectively.

In this contribution we will present the current status of integrating various HPC centers and cloud providers into the compute infrastructure at the Karlsruhe Institute of Technology as well as our experiences gained in a production environment.
Applying OSiRIS NMAL to Network Slices on SLATE
Authors: Musser Jeremy , Kissel Ezra , Swany Martin , Breen Joe , Stidd Jason , McKee Shawn , Meekhof Benjeman
Published: November 2020

The Network Management Abstraction Layer (NMAL) extends perfSONAR capabilities to include automated network topology discovery and tracking in the Unified Network Information Service (UNIS), and incorporate Software Defined Networking (SDN) into overall operations of the OSiRIS distributed Ceph infrastructure. We deploy perfSONAR components both within OSiRIS and at our “client” locations to allow monitoring and measuring the networks interconnecting science domain users and OSiRIS components. Topology discovery (using an SDN controller application) and Flange Network Orchestration (NOS) rules are used to dynamically manage network pathing in our testbed environments. NMAL components have been containerized to operate within the Services Layer at the Edge (SLATE) infrastructure, and we describe our experiences in packaging and deploying our services.
An automatic solution to make HTCondor more stable and easier
Authors: Shi Jingyan , Zou Jiaheng , Hu Qingbao , Jiang Xiaowei , Ou Ge
Published: November 2020

HTCondor has been widely adopted by HEP clusters to provide high-level scheduling performance. Unlike other schedulers, HTCondor provides loose management of the worker nodes. We developed a maintenance automation tool called “HTCondor MAT” that focuses on dynamic resource management and automatic error handling. A central database records all worker node information, which is sent to the worker node for the startd configuration. If an error happens for the worker node, the node information stored in the database is updated and the worker node is reconfigured with the new node information. The new configuration stops the startd from accepting error-related jobs until the worker node recovers. The MAT has been deployed in the IHEP HTC cluster to provide a central way to manage the worker nodes and remove the impacts of errors on the worker nodes automatically.
International Particle Physics Masterclasses – Current development to expand scope and global reach
Authors: Ould-Saada Farid
Published: November 2020

The International Particle Physics Outreach Group (IPPOG) is a network of scientists, science educators and communication specialists working across the globe in informal science education and outreach for particle physics. IPPOG’s flagship activity is the International Particle Physics Masterclass programme, which provides secondary students with access to particle physics data using dedicated visualisation and analysis software. Students meet scientists, learn about particle physics, accelerators and detectors, perform physics measurements and search for new phenomena, then compare results in an end-of-day videoconference with other classes. The most recent of these events was held from 7 March to 16 April 2019 with thousands of students participating in 332 classes held in 239 institutes from 54 countries around the world. We report on the evolution of Masterclasses in recent years, in both physics and computing scope, as well as in global reach.
Development of a Versatile, Full-featured Search Functionality for Indico
Authors: Constanta Penelope , Rind Ofer , Caballero Bejar Jose , Ferreira Pedro , Mönnich Adrian , Panero Pablo , De Oliveira Antunes Carina Rafaela , Chionis Koufakos Aristofanis
Published: November 2020

Indico, CERN’s popular open-source tool for event management, is in widespread use among facilities that make up the HEP community. It is extensible through a robust plugin architecture that provides features such as search and video conferencing integration. In 2018, Indico version 2 was released with many notable improvements, but without a full-featured search functionality that could be implemented easily outside of CERN. At both Fermi and Brookhaven National Laboratories, the user community viewed the lack of this popular feature as a significant impediment to deployment of the new software. In the meantime, CERN embarked upon a major redesign of their core search service, one that would also necessitate a rewrite of the Indico search interface. Seeing this pressing need, the two US labs decided to collaborate, with assistance from the CERN development team, on a project to develop the requisite search functionality for the larger user community. The resulting design exploits the simplified schema defined in the new CERN Search micro-service, based on Invenio and Elasticsearch, while still providing a flexible path to implementation for alternative backend search services. It is intended to provide a software package that can be installed easily and used out of the box, by anyone at any site. This paper will discuss the design choices and architectural challenges, and provide an overview of the deployment and use of these new plugins.
EuroEXA Custom Switch: an innovative FPGA-based system for extreme scale computing in Europe
Authors: Biagioni Andrea , Cretaro Paolo , Frezza Ottorino , Lo Cicero Francesca , Lonardo Alessandro , Paolucci Pier Stanislao , Pontisso Luca , Simula Francesco , Vicini Piero
Published: November 2020

EuroEXA is a major European FET research initiative that aims to deliver a proof-of-concept of a next generation Exa-scalable HPC platform. EuroEXA leverages on previous projects results (ExaNeSt, ExaNoDe and ECOSCALE) to design a medium scale but scalable, fully working HPC system prototype exploiting state-of-the-art FPGA devices that integrate compute accelerators and low-latency high-throughputnetwork.

Exascale-class systems are expected to host a very large number of computing nodes, from 104 up to 105, so that capability and performances of the interconnect architecture are critical to achieve high computing efficiency at this scale. In this perspective, EuroEXA enhances the ExaNet architecture, inherited by the ExaNeSt project, and introduces a multi-tier, hybrid topology network built on top of an FPGA-integrated Custom Switch that provides high throughput and low inter-node traffic latency for the different layers of the network hierarchy.

Deployment of a few testbeds is planned, with incremental complexity and equipped with complete software stack and runtime environment, to support the integration and test of the network design and to allow for evaluation of system performance and scalability through benchmarks based on real HPC applications. Design and integration activities are ongoing and the first small scale prototype (50 nodes) is expected to be completed in fall 2020 followed, one year later, by the deployment of the larger prototype (250/500 nodes).
Particle Track Reconstruction with Quantum Algorithms
Authors: Tüysüz Cenk , Carminati Federico , Demirköz Bilge , Dobos Daniel , Fracas Fabio , Novotny Kristiane , Potamianos Karolos , Vallecorsa Sofia , Vlimant Jean-Roch
Published: November 2020

Accurate determination of particle track reconstruction parameters will be a major challenge for the High Luminosity Large Hadron Collider (HL-LHC) experiments. The expected increase in the number of simultaneous collisions at the HL-LHC and the resulting high detector occupancy will make track reconstruction algorithms extremely demanding in terms of time and computing resources. The increase in number of hits will increase the complexity of track reconstruction algorithms. In addition, the ambiguity in assigning hits to particle tracks will be increased due to the finite resolution of the detector and the physical “closeness” of the hits. Thus, the reconstruction of charged particle tracks will be a major challenge to the correct interpretation of the HL-LHC data. Most methods currently in use are based on Kalman filters which are shown to be robust and to provide good physics performance. However, they are expected to scale worse than quadratically. Designing an algorithm capable of reducing the combinatorial background at the hit level, would provide a much “cleaner” initial seed to the Kalman filter, strongly reducing the total processing time. One of the salient features of Quantum Computers is the ability to evaluate a very large number of states simultaneously, making them an ideal instrument for searches in a large parameter space. In fact, different R&D initiatives are exploring how Quantum Tracking Algorithms could leverage such capabilities. In this paper, we present our work on the implementation of a quantum-based track finding algorithm aimed at reducing combinatorial background during the initial seeding stage. We use the publicly available dataset designed for the kaggle TrackML challenge.
Accelerate Scientific Deep Learning Models on Heterogeneous Computing Platform with FPGA
Authors: Jiang Chao , Ojika David , Vallecorsa Sofia , Kurth Thorsten , Prabhat  , Patel Bhavesh , Lam Herman
Published: November 2020

AI and deep learning are experiencing explosive growth in almost every domain involving analysis of big data. Deep learning using Deep Neural Networks (DNNs) has shown great promise for such scientific data analysis applications. However, traditional CPU-based sequential computing without special instructions can no longer meet the requirements of mission-critical applications, which are compute-intensive and require low latency and high throughput. Heterogeneous computing (HGC), with CPUs integrated with GPUs, FPGAs, and other science-targeted accelerators, offers unique capabilities to accelerate DNNs. Collaborating researchers at SHREC1at the University of Florida, CERN Openlab, NERSC2at Lawrence Berkeley National Lab, Dell EMC, and Intel are studying the application of heterogeneous computing (HGC) to scientific problems using DNN models. This paper focuses on the use of FPGAs to accelerate the inferencing stage of the HGC workflow. We present case studies and results in inferencing state-of-the-art DNN models for scientific data analysis, using Intel distribution of OpenVINO, running on an Intel Programmable Acceleration Card (PAC) equipped with an Arria 10 GX FPGA. Using the Intel Deep Learning Acceleration (DLA) development suite to optimize existing FPGA primitives and develop new ones, we were able accelerate the scientific DNN models under study with a speedup from 2.46x to 9.59x for a single Arria 10 FPGA against a single core (single thread) of a server-class Skylake CPU.
Künstliche Sauerstofftransporter können mehr als Sauerstoff liefern
Authors: Bäumler Hans
Published: November 2020

Zum gegenwärtigen Zeitpunkt ist in der EU und den USA kein artifizieller Sauerstofftransporter zugelassen. Hämoglobin-basierte Sauerstoff-Carrier (HBOC) sind bereits seit Jahrzehnten Gegenstand wissenschaftlicher Untersuchungen. Ein wesentliches Hindernis bei der Zulassung war bisher der Anspruch der Entwickler, einen universell einsetzbaren Blutersatz zu produzieren. Die Beschränkung auf eine Indikation scheint erfolgversprechender zu sein. Der Ansatz, nicht nur Sauerstoff von der Lunge zum Gewebe, sondern auch der Abtransport von Kohlendioxid vom Gewebe zur Lunge zu transportieren, der effektiver als mit Erythrozyten durchgeführt werden kann, erscheint besonders attraktiv. Aufgrund vielversprechender präklinischer sowie klinischer Untersuchungen besteht die Hoffnung, dass in absehbarer Zeit auch in der EU künstliche Sauerstofftransporter für therapeutische Zwecke zur Verfügung stehen werden.
Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of artificial intelligence: a pilot study
Authors: Ebigbo Alanna , Mendel Robert , Rückert Tobias , Schuster Laurin , Probst Andreas , Manzeneder Johannes , Prinz Friederike , Mende Matthias , Steinbrück Ingo , Faiss Siegbert , Rauber David , de Souza Luis A. , Papa João P. , Deprez Pierre H. , Oyama Tsuneo , Takahashi Akiko , Seewald Stefan , Sharma Prateek , Byrne Michael F. , Palm Christoph , Messmann Helmut
Published: November 2020

Background The accurate differentiation between T1a and T1b Barrett’s-related cancer has both therapeutic and prognostic implications but is challenging even for experienced physicians. We trained an artificial intelligence (AI) system on the basis of deep artificial neural networks (deep learning) to differentiate between T1a and T1b Barrett’s cancer on white-light images.

Methods Endoscopic images from three tertiary care centers in Germany were collected retrospectively. A deep learning system was trained and tested using the principles of cross validation. A total of 230 white-light endoscopic images (108 T1a and 122 T1b) were evaluated using the AI system. For comparison, the images were also classified by experts specialized in endoscopic diagnosis and treatment of Barrett’s cancer.

Results The sensitivity, specificity, F1 score, and accuracy of the AI system in the differentiation between T1a and T1b cancer lesions was 0.77, 0.64, 0.74, and 0.71, respectively. There was no statistically significant difference between the performance of the AI system and that of experts, who showed sensitivity, specificity, F1, and accuracy of 0.63, 0.78, 0.67, and 0.70, respectively.

Conclusion This pilot study demonstrates the first multicenter application of an AI-based system in the prediction of submucosal invasion in endoscopic images of Barrett’s cancer. AI scored equally to international experts in the field, but more work is necessary to improve the system and apply it to video sequences and real-life settings. Nevertheless, the correct prediction of submucosal invasion in Barrett’s cancer remains challenging for both experts and AI.
Recurrent motion in the fractional complex Ginzburg–Landau equation
Authors: Cheng Ming
Published: November 2020

This article concerns recurrent motion in the fractional complex Ginzburg–Landau equation with a small recurrent force. By using Galerkin’s method and energy estimate method, we obtain the existence of the bounded solutions, periodic solutions, quasiperiodic solutions, almost periodic solutions, and almost automorphic solutions under suitable assumptions.
Physicochemical parameters that underlie inkjet printing for medical applications
Authors: Azizi Machekposhti Sina , Movahed Saeid , Narayan Roger J.
Published: November 2020

One of the most common types of 3D printing technologies is inkjet printing due to its numerous advantages, including low cost, programmability, high resolution, throughput, and speed. Inkjet printers are also capable of fabricating artificial tissues with physiological characteristics similar to those of living tissues. These artificial tissues are used for disease modeling, drug discovery, drug screening, and replacements for diseased or damaged tissues. This paper reviews recent advancements in one of the most common 3D printing technologies, inkjet dispensing. We briefly consider common printing techniques, including fused deposition modeling (FDM), stereolithography (STL), and inkjet printing. We briefly discuss various steps in inkjet printing, including droplet generation, droplet ejection, interaction of droplets on substrates, drying, and solidification. We also discuss various parameters that affect the printing process, including ink properties (e.g., viscosity and surface tension), physical parameters (e.g., internal diameter of printheads), and actuation mechanisms (e.g., piezoelectric actuation and thermal actuation). Through better understanding of common 3D printing technologies and the parameters that influence the printing processes, new types of artificial tissues, disease models, and structures for drug discovery and drug screening may be prepared. This review considers future directions in inkjet printing research that are focused on enhancing the resolution, printability, and uniformity of printed structures.
Capturing the nuclear quantum effects in molecular dynamics for lattice thermal conductivity calculations: Using ice as example
Authors: Luo Ripeng , Yu Kuang
Published: November 2020

Molecular dynamics (MD) is a powerful (and the most viable) tool to compute the thermal conductivities of solid disordered materials. However, conventional classical MD fails to describe the nuclear quantum effects (NQEs), so it may give inaccurate results for light materials at low temperatures. While the importance of NQE has been widely acknowledged, yet we do not have a fully reliable method to account for NQE in the MD thermal conductivity calculations. In this work, we will investigate and analyze the performances of a number of path-integral-based quantum MD methods, using ordered ice as a test case. To establish the validity of these methods, we will compare the MD results with the lattice dynamics results, in both classical and quantum limits. Through such a comparison, we will show that methods such as ring polymer MD stand as a good approach for a complex solid with short phonon lifetimes but could be problematic when describing long-living acoustic phonons. In addition, we will show that the rigid water model, which is the state-of-the-art model in the studies of ice/water systems, fails to capture most of the NQEs in ice thermal conductivity. Neglecting librational and translational NQEs leads to essential errors, which clearly demonstrates the importance of a true quantum simulation method that treats all modes at a consistent quantum level.
Kinetics of lithium electrodeposition and stripping
Authors: Sripad Shashank , Korff Daniel , DeCaluwe Steven C. , Viswanathan Venkatasubramanian
Published: November 2020

Electrodeposition and stripping are fundamental electrochemical processes for metals and have gained importance in rechargeable Li-ion batteries due to lithium metal electrodes. The electrode kinetics associated with lithium metal electrodeposition and stripping is crucial in determining the performance at fast discharge and charge, which is important for electric vertical takeoff and landing (eVTOL) aircraft and electric vehicles (EV). In this work, we show the use of Marcus–Hush–Chidsey (MHC) kinetics to accurately predict the Tafel curve data from the work of Boyle et al. [ACS Energy Lett. 5(3), 701 (2020)]. We discuss the differences in predictions of reorganization energies from the Marcus–Hush and the MHC models for lithium metal electrodes in four solvents. The MHC kinetic model is implemented and open-sourced within Cantera. Using the reaction kinetic model in a pseudo-2D battery model with a lithium anode paired with a LiFePO4 cathode, we show the importance of accounting for the MHC kinetics and compare it to the use of Butler–Volmer and Marcus–Hush kinetic models. We find significant deviation in the limiting currents associated with reaction kinetics for the three different rate laws for conditions of fast charge and discharge relevant for eVTOL and EV, respectively.
Growth of high-quality one-inch free-standing heteroepitaxial (001) diamond on (112¯0) sapphire substrate
Authors: Kim Seong-Woo , Kawamata Yuki , Takaya Ryota , Koyama Koji. , Kasu Makoto
Published: November 2020

One-inch free-standing (001) diamond layers on a (112¯0) (a-plane) sapphire substrate with an Ir buffer layer (Kenzan Diamond®) were grown. The full-width at half maximum values of (004) and (311) x-ray rocking curves were 113.4 and 234.0 arc sec, respectively. The dislocation density of the substrates was 1.4 × 107 cm−2, determined by plan-view transmission electron microscopy observation. These values are much lower than the reported values among heteroepitaxial diamonds. Furthermore, x-ray pole figure measurements showed four symmetry of the crystal, showing single crystallinity without any twinning. The curvature radius of diamond was measured to be 90.6 cm, which is much larger than previous values, ca. 20 cm. Surprisingly, a cubic-lattice (001) diamond crystal was epitaxially grown on a trigonal-lattice (112¯0) sapphire substrate. However, we found that the epitaxial relation is diamond (001) [110]//Ir (001) [110]//sapphire (112¯0) [0001]. Now, high-quality one-inch diamond wafers will be available as a substrate used for diamond electronic devices.
Dynamic azopolymeric interfaces for photoactive cell instruction
Authors: De Martino Selene , Netti Paolo Antonio
Published: November 2020

The ability to affect a wide range of biophysical properties through the use of light has led to the development of dynamic cell instructive materials. Using photoresponsive materials such as azopolymers, smart systems that use external, minimally damaging, light irradiation can be used to trigger specific surface morpho-physical properties in the presence of living cells. The interaction of light with an azopolymer film induces a mass migration phenomenon, allowing a variety of topographic patterns to be embossed on the polymeric film. Photoisomerization induces conformational changes at the molecular and macroscopic scale, resulting in light-induced variations of substrate morphological, physical, and mechanical properties. In this review, we discuss the photoactuation of azopolymeric interfaces to provide guidelines for the engineering and design of azopolymer films. Laser micropatterning for the modulation of azopolymer surfaces is examined as a way to diversify the capabilities of these polymers in cellular systems. Mass migration effects induced by azopolymer switching provides a foundation for performing a broad range of cellular manipulation techniques. Applications of azopolymers are explored in the context of dynamic culture systems, gaining insight into the complex processes involved in dynamic cell-material interactions. The review highlights azopolymers as a candidate for various applications in cellular control, including cell alignment, migration, gene expression, and others. Recent advances have underlined the importance of these systems in applications regarding three-dimensional cell culture and stem cell morphology. Azopolymers can be used not only to manipulate cells but also to probe for mechanistic studies of cellular crosstalk in response to chemical and mechanical stimuli.
Stabilized motion of a freely falling bristled disk
Authors: Lee Minhyeong , Lee Seung Hun , Kim Daegyoum
Published: November 2020

Several tiny insects have peculiar porous wings composed of many bristles and perform an interesting passive flight known as parachuting. Despite numerous studies on the freefall of objects such as disks, the aerodynamic principles of the effects of a bristled configuration on the parachuting motion under external disturbances remain unexplored. Here, we experimentally investigate freely falling bristled disks over a wide range of Reynolds numbers by changing the number of bristles and the initial orientation angle and compare their kinematics with those of a full circular disk with no bristles. Given the same diameter and moment of inertia, bristled disks with a smaller area have a steady-state flow field similar to that of a circular disk by virtue of the presence of a fully formed virtual fluid barrier at low-Reynolds numbers. However, in the initial transient phase after release, the bristled disks show different damped oscillatory motions from a circular disk. Regardless of their initial orientation angle, the lateral and angular deviations of the bristled disks are smaller than those of the circular disk, producing a more stable freefall. This trend is also observed even for higher Reynolds numbers, where the bristled wings are known to be ineffective from the perspective of aerodynamic performance. By considering the vorticity fields around the disk, we suggest two vortex-related mechanisms that account for the stable falling of the bristled disk, namely, the formation of more symmetric vortex structures and the location of vortex cores closer to the disk center.
Highly stable threshold voltage in GaN nanowire FETs: The advantages of p-GaN channel/Al2O3 gate insulator
Authors: Ruzzarin Maria , De Santi Carlo , Yu Feng , Fatahilah Muhammad Fahlesa , Strempel Klaas , Wasisto Hutomo Suryo , Waag Andreas , Meneghesso Gaudenzio , Zanoni Enrico , Meneghini Matteo
Published: November 2020

We present an extensive investigation of the charge-trapping processes in vertical GaN nanowire FETs with a gate-all-around structure. Two sets of devices were investigated: Gen1 samples have unipolar (n-type) epitaxy, whereas Gen2 samples have a p-doped channel and an n-p-n gate stack. From experimental results, we demonstrate the superior performance of the transistor structure with a p-GaN channel/Al2O3 gate insulator in terms of dc performance. In addition, we demonstrate that Gen2 devices have highly stable threshold voltage, thus representing ideal devices for power electronic applications. Insight into the trapping processes in the two generations of devices was obtained by modeling the threshold voltage variations via differential rate equations.
The deflection angle between a wind-forced surface current and the overlying wind in an ocean with vertically varying eddy viscosity
Authors: Constantin Adrian , Dritschel David G. , Paldor Nathan
Published: November 2020

The angle between the wind stress that overlies the ocean and the resulting current at the ocean surface is calculated for a two-layer ocean with uniform eddy viscosity in the lower layer and for several assumed eddy viscosity profiles in the upper layer. The calculation of the deflection angle is greatly simplified by transforming the linear, second-order, vertical structure equation to its associated nonlinear, first-order, Riccati equation. The transformation to a Riccati equation can be used as an alternate numerical scheme, but its main advantage is that it yields analytic expressions for several eddy viscosity profiles.
Kinetic energy deposited into a nanodroplet, cluster, or molecule in a sticking collision with background gas
Authors: Liang Jiahao , Kresin Vitaly V.
Published: November 2020

In processes when particles such as nanodroplets, clusters, or molecules move through a dilute background gas and undergo capture collisions, it is often important to know how much translational kinetic energy is deposited into the particles by these pick-up events. For sticking collisions with a Maxwell–Boltzmann gas, an exact expression is derived, which is valid for arbitrary relative magnitudes of the particle and thermal gas speeds.