Details Emerging on Japan’s Future Exascale System

By Nicole Hemsoth

March 18, 2014

The Big Data and Extreme Computing meeting in Fukuoka, Japan concluded recently, pushing a great deal of information about international progress toward exascale initiatives into the global community.

As the host country, Japan had ample opportunity to gather many of the researchers building out the next incarnation of the K Computer, which is expected to be the country’s first exascale system—a $1.38 billion undertaking that’s already underway with expected installation in 2019 and full-steam production in 2020.

According to the roadmap put forth by Yoshio Kawaguchi from Japan’s Office for Promotion of Computing Science/MEXT, basic development for the future system is swiftly moving on software, accelerator, processor and scientific project planning fronts. Fujitsu, Hitachi and NEC are key vendors providing the system and support, along with technical staff at the University of Tokyo, the University of Tsukuba, the Tokyo Institute of Technology, Tohoku University and of course, at RIKEN, site of the K Computer and future hub of its successor.

Called “postK” in reference to its ability to step up the power of the original former top system, K, the timeline for the exascale system is laid out as a projection–with additional research notes (summarized below) to highlight various tracks of the early development and system/stack design.

Japan_Exascale_RoadmapJapan has its sights set on a number of potential problems that might be solved on postK, including the development of safer cars, the evolution of drugs with mitigated or reduced side effects, better prediction and responses to natural disasters, and specific projects, like the development of better batteries, the creation of electronic devices using novel materials, and the enhanced ability to kick galaxy simulation up several (thousand) notches.

JapanExascaleChart

ExascaleChart2

Of course, to do all of this at a reasonable cost is going to take some serious innovation. A few of the key researchers behind the components to building postK shared details, including Dr. Mitsushisa Sato from the Center for Computational Sciences at the University of Tsukba and team leader for the Programming Environment Research Team behind the K Computer at RIKEN.

His work is centered around optimal accelerators for massive heterogeneous systems, which has led to the creation of what the team calls an “extreme SIMD architecture” designed for compute oriented applications. This involves tightly coupled accelerators and a few unique memory refinements, including the addition of high bandwidth memory (HBM in the chart below).

This architecture would be designed to tackle molecular dynamics and N-body-type simulations as well as stencil apps and according to Sato, will aim for high performance in the area of around 10 teraflops per chip using a 10nm silicon technology that will arrive somewhere in the 2018-2020 timeframe. While that’s not staggering when you really think about it, the real story seems to be (at this point anyway) that most of the crunch is being handled by the on-board accelerator with the added weight of the memory on the same package and associated networking.

Accelerator_Arch

Sato and team are exploring possible programming models for this approach via a C extension for the in-the-weeds aspects, an OpenACC-based model for stencil applications to help ease porting existing codes, a DSL and application framework for building with as well as the option of OpenCL. There is no mention of CUDA here, which should likely tell you something about the nature of the accelerator. Again, as with all aspects of this article, we’ll be following up as soon as we can secure more information.

ArchitecturesOn the processor front, this is again seen as a natural evolution of the K system. According to Yutaka Ishikawa from the University of Tokyo, the team will carry over lessons learned with the general processor environment to target far greater efficiency and to meet a software stack that’s designed for both the proposed and commodity-based systems. The ridiculously bright yellow chart on the left shows the various processor approaches they’ve been testing during their current cycles.

In a presentation from the application and system feasibility study teams, they noted the many parallels in terms of challenges and potential problems the system could solve between K and the exascale system of 2020. The K Computer, which was put into production in 2011, currently has over 1,431 users and is running around 136 projects. Each of the sites in Japan’s national infrastructure is dedicated to a specific strategic application area (although not exclusively running projects in the domain). At RIKEN the K system is devoted in particular to life sciences and drug design problems. Other sites are focused on materials science, climate and geosciences, manufacturing and astrophysics. The system has supported two notable Gordon Bell prizes since its inception, in addition to topping the Top 500 list in 2011.

Keep in mind that the United States is a partner on the software side of the project. As Kawaguchi’s slide highlights, the partnership will continue into the next phases of system development. The team notes that “international collaboration for system software has been considered”

Exascale_Partnership_Japan

We’ll be bringing much more insight into this story as soon as we’re able to secure it but we did want to point to the details as soon as possible. You can view more about these and other presentations around exascale (not to mention a lot of talk about big data) at the main site, where the presentations have just gone live: http://www.exascale.org/bdec/agenda/fukuoka-japan

Our thanks to Dr. Jack Dongarra to the early insight he was able to provide. Follow-up coming soon, stay tuned…

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire