Research towards
Next-Gen Supercomputing Systems
Fujitsu Next Generation Computing Infrastructure Collaborative Research Cluster
In October 2022, Tokyo Institute of Technology and Fujitsu have established the "Fujitsu Next Generation Computing Infrastructure
Collaborative Research Cluster" at Tokyo Tech's Suzukakedai Campus. The purpose is to realize a next-generation computing infrastructure
capable of extremely large-scale data processing and simulations based on AI and high-performance computing (HPC) technologies.
System Infrastructure Accommodating Interactive HPC
Basic research

Applied research Expansion and enhancement of various newtechnologies for product applica�ons

 Crea�on of new applica�ons, middleware, andarchitectures as well as new applica�on areas

 Joint hardware and so�ware development basedon applica�on characteris�cs

 HPC pla�orm for new societal ﬁelds using HPC
compu�ng and HPC technology

Interactive
Data Analysis

Motivation:

Visualization of
Simulated Results

Deep Learning
Based Analysis

Usage of HPC system is widespreading, including interactive

Next-genera�on compu�ng infrastructureor realtime jobs. In order fulfill

AI×HPCMiddleware
HPC libraries

Architectures
Networks
Edge collabora�onrequirements, next-gen scheduling

Compu�ng pla�orm systems

Crea�ng pla�orms to solve various societal issues

Leader:Innova�on and DX on the front lines ofmanufacturing

Shared HPC System
100000

Medical innova�ons
through genomics andIT-based drug discovery

Maximum Rela�ve Turnaround

Zero emissions

method is required.

Hidehiko Masuhara (Tokyo Tech)

Sub-leaders: Naoki Akaboshi (Fujitsu), Toshio Endo (Tokyo Tech)
Members (partial):
Masahiro Miwa (Fujitsu)

Isao Ono (Tokyo Tech)

Miwa Ueki (Fujitsu)

Ryo Onishi (Tokyo Tech)

Takafumi Kanamori (Tokyo Tech)

Ryuichi Sakamoto (Tokyo Tech)

Rio Yokota (Tokyo Tech)

Akihiro Nomura (Tokyo Tech)

Batch Jobs

Intr Jobs

100001000100101Tradi�onal

Separate Queue(2% for Intr Jobs)

OSub Schedule(Mul�plicity 4)

Scheduling simulation shows Oversubscribing
Interactive jobs have divergent CPU usage
pattern. Data are from TSUBAME3(OSub) scheduling drastically improves
responsiveness of jobs.
[Minami et al. IEEE HPEC 2023]

Scalable Tracing for
Post-5G Distributed System

Research and Study ofOperation Technologies
Collabolative research with U. Tokyo, RIKEN R-CCS, NII, and other institutes.

Collabolative research with AIST, and other institutes.

The Feasibility Study (FS) for next-generation computing infrastructure In Post-5G era, data analysis systems are more distributed andby MEXT, Japan was started on August 2022, and we are studying

heterogeneous including edge devices. In order to monitor andthe field of operation technology of HPC. We aim to offer amanage such systems, scalable distributed tracer is required.

next-generation system that can serve as a research DX infrastructure

Approaches:with an advanced digital twin to provide a platform for solving issues to - Collection methods of tracing data optimized for each system layer
realize broad SDGs.
Carbon Neutrality- Cooperation among multiple layers and hierarchical distibuted storage- Data compression and efficient storage using techniques- Procurement of green (lowhttps://datacenterfrontier.com/
waste-heat-utilization-data-center-industry/carbon emission) electricity

H2- Energy conservation of the entire

Li-ion Battery Hydrogengeneration

facility including HPC systems

Energy storage
equipment

Towards scalable tracing, initial

HPC datacenter- Promotion of reuse of waste heat

Reuse of waste heatfrom HPC systems

Facility and Equipment- Investigation of hot-water cooling technology- Analysis and demonstration of power-saving
operation by real-time power consumption monitoring

Initial Evaluation:

Resource Management- Coordinated resource management technology
among major supercomputers- Integration with the cloud (cloud bursting)- Networking technologies to enable coordination

evaluation on response time withseveral system configurations has
been done to investigate bottleneck.

Large gap due to with orwithout Kubernetes- The Bookinfo microservice has
been deployed and measured.
- Multiple connections using wrk2 are created and varying numbers ofrequests are sent in parallel.
Costs introduced by Kubernetes (K8s) are observed.

Data Leverage
Society 5.0, SDGs, Research DX

This work is supported by “Research and Development Project of the Enhanced Infrastructures for Post-5G
Information and Communication Systems” (JPNP20017), commissioned by the New Energy and Industrial
Technology Development Organization (NEDO).

HPCI federated operation

http://www.gsic.titech.ac.jp/sc23