China’s Tianhe-2A will Use Proprietary Accelerator and Boast 95 Petaflops Peak

By John Russell

September 25, 2017

The details of China’s upgrade to Tianhe-2 (MilkyWay-2) – now Tianhe-2A – were revealed last week at the Third International High Performance Computing Forum (IHPCF2017) in China. The Tianhe-2A will use a proprietary accelerator (Matrix-2000), a proprietary network, and provide support for OpenMP and OpenCL. The upgrade is about 25 percent complete and expected to be fully functional by November 2017 according to a report by Jack Dongarra who attended the meeting and has written a fairly detailed summary.

“The most significant enhancement to the system is the upgrade to the TianHe-2 nodes; the old Intel Xeon Phi Knights Corner (KNC) accelerators will be replaced with a proprietary accelerator called the Matrix-2000. In addition, the network has been enhanced, the memory increased, and the number of cabinets expanded. The completed system, when fully integrated with 4,981,760 cores and 3.4 PB of primary memory, will have a theoretical peak performance of 94.97 petaflops, which is roughly double the performance of the existing Tianhe-2 system. NUDT also developed the heterogeneous programming environment for the Matrix-20002 with support for OpenMP and OpenCL,” writes Dongarra (Report on The TianHe-2A System).

Dongarra told HPCwire, “The Matrix-2000 was designed by the NUDT people. They claim it was fabbed in China. They did not want to have the manufacturing process disclosed.”

The Tianhe-2 vaulted China atop the Top500 list in June of 2013 (with 33.9 petaflops Linpack performance) where it stayed until June 2016 when China’s Sunway TaihuLight topped the list with a Linpack of 93 petaflops. The Sunway was China’s first supercomputer to use homegrown processors (see HPCwire article, China Debuts 93-Petaflops ‘Sunway’ with Homegrown Processors). China has held the top two positions ever since.

“The TianHe-2A is one of the three prototype systems for Exascale in China. The others are the TaiHu Light in Wuxi and the Sugon Machine based on X86 architecture,” said Dongarra.

Each of the 17,792 Tianhe-2A compute nodes will use two of Intel’s Ivy Bridge CPUs (12 cores clocked at 2.2 GHz) and two of the new NUDT-designed Matrix-2000 accelerators (128 cores clocked at 1.2 GHz). This combination results in a compute system with 35,584 Ivy Bridge CPUs, 35,584 Matrix-2000 accelerators, reports Dongarra.

Introduction of the China-developed Matrix-2000 accelerator showcases China’s continued progress towards technology independence.

As described by Dongarra, each Matrix- 2000 has 128 compute cores clocked at 1.2 GHz, achieving 2.4576 teraflops of peak performance. The peak power dissipation is about 240 watts and the dimensions are 66mm by 66mm. The accelerator itself is configured with four supernodes (SNs) that are connected through a scalable on-chip communication network. Each SN has 32 compute cores and complies with the cache coherence. The accelerator supports eight DDR4-2400 channels and is integrated with a ×16 PCI Express 3.0 endpoint port. The compute core is an in-order 8~12 stage reduced instruction set computer (RISC) pipeline extended with a 256-bit vector instruction set architecture (ISA). Two 256-bit vector functional units (VFUs) are integrated into each compute core, resulting in 16 double precision FLOPs per cycle. Thus, the peak performance of the Matrix-2000 can be calculated as: 4 SNs × 32 cores × 16 FLOPs per cycle × 1.2 GHz clock = 2.4576 Tflop/s.

As shown below, a TH-2A compute blade is composed of two parts: the CPM (left) and the APU (middle). The CPM integrates four Ivy Bridge CPUs, and the APU integrates four Matrix- 2000 accelerators. Each compute blade contains two heterogeneous compute nodes.

The TH-2A upgrades required the design and implementation of a heterogeneous computing software stack for the Matrix-2000 accelerator writes Dongarra. This software stack provides a compiling and execution environment for OpenMP 4.5 and OpenCL 1.2. The runtime software stack is illustrated in figure below.

“In kernel mode, there is a light-weight Linux-based operating system (OS), with the accelerator device driver embedded within it, running on the Matrix-2000 that provides device resource management and data communication with the host CPU through the PCI Express connection. The OS manages the computing cores through an elaborately designed thread pool mechanism, which enables task scheduling with low overhead and high efficiency.”

China’s rapid advance in supercomputing and its accelerated effort to build its own technology ecosystem has been a hot topic for some time. Dongarra captures the dynamics and technology achievement neatly his summary:

“In February 2015, the US Department of Commerce prevented some Chinese research groups from receiving Intel technology. The department cited concerns about nuclear research being performed on compute systems equipped with Intel components. The research centers affected include: NSCC-G, site of Tianhe-2; the National SC Center Tianjin, site of Tianhe-1A; the NUDT, developer; and the National SC Center Changsha, location of NUDT.

“At the 2015 International Supercomputing Conference (ISC) in Frankfurt, Yutong Lu, the director of the NSCC-G, described the TianHe-2A system (Figure 10). Most of what was shown in her slide in 2015 has been realized in the Matrix-2000 accelerator. They had hoped to replace the Intel KNC accelerator in their TH-2 with the Matrix-2000 by 2016. However, because of delays that has not happened until very recently.

“After the embargo on Intel components by the US Department of Commerce, it has taken NUDT about two years to design and implement a replacement for the Intel Xeon Phi KNC accelerator. Their replacement is about the same level of performance as the current generation of Intel’s Xeon Phi, known as Knights Landing (KNL). Equaling the performance of the state-of-the-art KNL chip and developing the accompanying software stack in such a short time is an impressive result.”

Last week’s IHPCF2017 meeting was sponsored by the Ministry of Science and Technology (MOST) and the National Science Foundation of China (NSFC), organized by NUDT, and hosted by the National Supercomputer Center in Guangzhou (NSCC-GZ); it was held on September 18–20, 2017 in Guangzhou, China. There were roughly 160 attendees, reported Dongarra.

Given this latest announcement, and speculation of what may be happening with the TaihuLight system, the SC17 conference in November should spark interesting discussion. Clearly the international jostling for sway in the race to pre- and full exascale machines continues to heat up.  Just last week, the U.S. Exascale Computing Project announced the retirement of Paul Messina as director and appointment of Doug Kothe as new director.

Expectations are high that Summit (Oak Ridge National Laboratory) will be at or near the top of the Top500 list. Likewise, there’s been speculation that Sierra (Lawrence Livermore National Laboratory) might be ready by then. It’s been awhile since the U.S. was top dog in the Top500. In any case, it will be interesting to see the next batch on LINPACK scores and what shuffling of the Top500 emerges.

Link to Dongarra’s excellent summary paper: https://www.dropbox.com/s/0jyh5qlgok73t1f/TH-2A-report.pdf?dl=0

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!

Empowering High-Performance Computing for Artificial Intelligence

April 19, 2024

Artificial intelligence (AI) presents some of the most challenging demands in information technology, especially concerning computing power and data movement. As a result of these challenges, high-performance computing Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

2024 Winter Classic: Texas Two Step

April 18, 2024

Texas Tech University. Their middle name is ‘tech’, so it’s no surprise that they’ve been fielding not one, but two teams in the last three Winter Classic cluster competitions. Their teams, dubbed Matador and Red Read more…

2024 Winter Classic: The Return of Team Fayetteville

April 18, 2024

Hailing from Fayetteville, NC, Fayetteville State University stayed under the radar in their first Winter Classic competition in 2022. Solid students for sure, but not a lot of HPC experience. All good. They didn’t Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use of Rigetti’s Novera 9-qubit QPU. The approach by a quantum Read more…

2024 Winter Classic: Meet Team Morehouse

April 17, 2024

Morehouse College? The university is well-known for their long list of illustrious graduates, the rigor of their academics, and the quality of the instruction. They were one of the first schools to sign up for the Winter Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it 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…

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…

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…

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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

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…

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…

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…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire