Fujitsu Continues HPC, AI Push

By Tiffany Trader

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu’s output. The Japanese multinational has made a raft of HPC and AI-related announcements over the last few weeks. One of the most interesting developments is the advance of a custom AI processor, the Deep Learning Unit (DLU). With only a brief appearance in a 2016 press release, a fuller picture emerged during the International Supercomputing Conference in June.

As revealed in a presentation from Fujitsu’s Takumi Maruyama (senior director, AI Platform business unit), the processor features mixed-precision optimizations (8-bit, 16-bit and 32-bit) and a low power consumption design, with a stated goal of achieving a 10x performance/per watt advantage compared to competitors. The target energy efficiency gain relies on Fujitsu’s “deep learning integer,” which the company says reaches effective precision (on par with 32-bit) using 8- and 16-bit data sizes. The approach is reminiscent of that used by Intel’s Knights Mill processor (see coverage here) with Intel claiming INT32 accuracy with INT16 inputs (using INT32 accumulated output).

Source: Fujitsu (2017)

The massively parallel chip employs a few large master cores connected to many Deep Learning Processing Units (DPUs). One DPU consists of 16 DPEs (Deep learning processing elements). The DPE includes a large register file and wide SIMD execution units. Linked with Fujitsu’s Tofu interconnect technology, the design is scalable for very large neural networks.

Fujitsu’s roadmap for the DLU includes multiple generations over time: a first-gen coprocessor is set to debut in 2018, followed by a second-gen embedded host CPU. More forward-looking are potential specialized processors targeting neuromorphic or combinatorial optimization applications.

Upcoming Installs

National Center for High-performance Computing (NCHC) headquarters

Also at ISC, Fujitsu announced it’s building a nearly 3.5 petaflops (peak) system for Taiwan’s National Center for High-performance Computing, National Applied Research Laboratories (NCHC). The supercomputer is expected to come online in May 2018, at which time it will become the fastest computer in the country.

“The new system will serve as the core platform for research and development in Taiwan, fostering the development and growth of Taiwan’s overall industries and economy,” said Fujitsu in an official statement. In addition to accelerating current research, there will be a focus on accommodating new research fields, such as AI and big data.

The 715 node warm water-cooled cluster will be equipped with Skylake processors and connected with Intel Omni-Path technology. Nvidia P100 GPUs will be installed on 64 nodes, providing over a third (1.35 petaflops) of total theoretical peak performance (3.48 petaflops).

The Information Technology at Kyushu University in Japan has also placed an order for a Fujitsu system, a 10-petaflopper (peak) that is scheduled for deployment in October.

“This system will consist of over 2,000 servers, including the Fujitsu Server PRIMERGY CX400, the next-generation model of Fujitsu’s x86 server….This will also be Japan’s first supercomputer system featuring a large-scale private cloud environment constructed on a front-end sub system, linked with a computational server of a back-end sub system through a high-speed file system,” according to the release.

The new supercomputer will be integrated with three existing HPC systems at the Research Institute for Information Technology. The goal is to create an environment that “extend[s] beyond the current large-scale computation and scientific simulations, to include usage and research that require extremely large-scale computation, such as AI, big data, and data science.”

New AI-Based Algorithm Monitors Heat Stress

As temperatures rise, the health of employees in active outdoor roles, for example security guards or delivery professionals, is threatened. In Japan, 400-500 workplace casualties are attributable to heat stroke each year, leading companies to take measures to safeguard employees working in extreme conditions.

Fujitsu has developed an algorithm to bolster summer safety in the workplace. Based on Fujitsu’s Human Centric AI platform, Zinrai, the algorithm estimates on-going heat stress in workers. Fujitsu will release the algorithm as part of its digital business platform, MetaArc, which uses IoT to support on-site safety management. It is also conducting an internal trial from June to September at its Kawasaki Plant.

Source: Fujitsu (2017)

Says the company, “Sites where security and other duties typically take place may be locations where workers are susceptible to heat stress. However, changes in physical condition vary according to the individual, making it difficult to take uniform measures. This newly developed algorithm makes it possible to estimate the accumulation of heat stress on a per person basis, to tailor ways to protect people based on individual conditions.”

Machine Learning Advances Lung Disease Diagnosis

Fujitsu Laboratories Ltd. in partnership with Fujitsu R&D Center Co., Ltd., has developed a technology to improve the diagnosis for a group of lung diseases that includes pneumonia and emphysema. The technology retrieves similar disease cases from a computed tomography (CT) database based on abnormal shadows implicated in these disease states. The technology is especially needed for diffuse lung diseases like pneumonia, where the abnormal shadows are spread throughout the organ in all directions. These three-dimensional problems require a great deal of knowledge and experience on the clinician’s part to interpret and diagnose.

Source: Fujitsu (2017)

As explained by Fujitsu “the technology automatically separates the complex interior of the organ into areas through image analysis, and uses machine learning to recognize abnormal shadow candidates in each area. By dividing up the organ spatially into periphery, core, top, bottom, left and right, and focusing on the spread of the abnormal shadows in each area, it becomes possible to view things in the same way doctors do when determining similarities for diagnosis.”

Early studies using real-world data indicate a high-accuracy for the approach, which has the potential to save lives by reducing the time it takes to achieve a correct diagnosis.

Promoting open data usage in the Japanese Government

On June 28, Fujitsu announced that it will be part of a project run by the Cabinet Secretariat’s National Strategy Office of Information and Communications Technology to promote the use of open data held by the national or regional public organizations. The goal is to make open data, such as population statistics, industry compositions, and geographic data, more accessible and by doing so strengthen national competitiveness.

Fujitsu will leverage its Zinrai platform to develop a test system that can laterally search for data across multiple government systems, relating texts that have the same meaning. The system will also “learn” from users’ search results such that it can fine-tune its suggestions.

Source: Fujitsu (2017)

The study, “Creating an AI-Based Multi-Database Search and Best-Response Suggestion System (Research Study on Increasing Usability of Data Catalog Sites),” will run through until December 22, 2017. Fujitsu expects the trial to result in a proposal to the Strategy Office of Information and Communications Technology for implementation.

The Zinrai AI framework:

Source: Fujitsu (2016)

 

Subscribe to HPCwire's Weekly Update!

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

Cray+Azure: Can Cloud Propel Supercomputing?

October 23, 2017

Cray and Microsoft today announced they will offer dedicated Cray supercomputers (the XC and CS-Storm lines) inside the Azure platform allowing customers to run their HPC and AI applications alongside their other cloud w Read more…

By Tiffany Trader

2017 Gordon Bell Prize Finalists Named

October 23, 2017

The three finalists for this year’s Gordon Bell Prize in High Performance Computing have been announced. They include two papers on projects run on China’s Sunway TaihuLight system and a third paper on 3D image recon Read more…

By John Russell

Data Vortex Users Contemplate the Future of Supercomputing

October 19, 2017

Last month (Sept. 11-12), HPC networking company Data Vortex held its inaugural users group at Pacific Northwest National Laboratory (PNNL) bringing together about 30 participants from industry, government and academia t Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Transforming Genomic Analytics with HPC-Accelerated Insights

Advancements in the field of genomics are revolutionizing our understanding of human biology, rapidly accelerating the discovery and treatment of genetic diseases, and dramatically improving human health. Read more…

AI Self-Training Goes Forward at Google DeepMind

October 19, 2017

DeepMind, Google’s AI research organization, announced today in a blog that AlphaGo Zero, the latest evolution of AlphaGo (the first computer program to defeat a Go world champion) trained itself within three days to play Go at a superhuman level (i.e., better than any human) – and to beat the old version of AlphaGo – without leveraging human expertise, data or training. Read more…

By Doug Black

Cray+Azure: Can Cloud Propel Supercomputing?

October 23, 2017

Cray and Microsoft today announced they will offer dedicated Cray supercomputers (the XC and CS-Storm lines) inside the Azure platform allowing customers to run Read more…

By Tiffany Trader

Data Vortex Users Contemplate the Future of Supercomputing

October 19, 2017

Last month (Sept. 11-12), HPC networking company Data Vortex held its inaugural users group at Pacific Northwest National Laboratory (PNNL) bringing together ab Read more…

By Tiffany Trader

AI Self-Training Goes Forward at Google DeepMind

October 19, 2017

DeepMind, Google’s AI research organization, announced today in a blog that AlphaGo Zero, the latest evolution of AlphaGo (the first computer program to defeat a Go world champion) trained itself within three days to play Go at a superhuman level (i.e., better than any human) – and to beat the old version of AlphaGo – without leveraging human expertise, data or training. Read more…

By Doug Black

Student Cluster Competition Coverage New Home

October 16, 2017

Hello computer sports fans! This is the first of many (many!) articles covering the world-wide phenomenon of Student Cluster Competitions. Finally, the Student Read more…

By Dan Olds

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan Read more…

By John Russell

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Leading Solution Providers

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

  • arrow
  • Click Here for More Headlines
  • arrow
Share This