AMD Courts HPC with 11.5 Teraflops Instinct MI100 GPU

By Tiffany Trader

November 16, 2020

AMD today announced the new MI100 Instinct accelerator, billing it as “the world’s fastest HPC GPU” with 11.5 teraflops of peak double-precision floating point performance. A follow on to the MI50 and MI60 Instinct accelerators launched two years ago (the “world’s first 7nm datacenter GPUs”), the MI100 is also manufactured on TSMC’s 7nm process, but boasts twice as many compute units as the previous generation within the same 300-watt power envelope.

Block diagram of the AMD Instinct MI100 accelerator, powered by the AMD CDNA architecture

The MI100 GPU is the first to incorporate AMD’s Compute DNA (CDNA) architecture with 120 CUs organized into four arrays. An evolution of AMD’s earlier GCN architecture, CDNA includes new matrix core engines that boost computational throughput for different numerical formats.

Going down the spec sheet, the MI100 offers 46.1 teraflops peak single-precision matrix (FP32), 23.1 teraflops peak single-precision (FP32), 184.6 teraflops peak half-precision (FP16) floating-point performance, and 92.3 peak teraflops of bfloat16 performance.

The new AMD matrix core technology provides the MI100 with 7x greater peak half-precision floating point performance compared to the MI50, according to AMD. Brad McCredie (corporate vice president of datacenter GPU and accelerated processing at AMD) told HPCwire the company is exploring other emerging numerical formats that target AI and ML workloads, but doesn’t want to get too far out in front of the industry.

AMD’s MI100 GPU presents a competitive alternative to Nvidia’s A100 GPU, rated at 9.7 teraflops of peak theoretical performance. However, the A100 is returning even higher performance than that on its FP64 Linpack runs. (Yes, you heard right.) The A100 GPU is achieving ~12 double-precision Linpack teraflops (see Selene, for example), and Nvidia confirmed to me they use a different double-precision peak for their marketing material and for their Top500 rMax (9.7 versus 15.1 teraflops, respectively).

As new numerical formats optimized for AI/ML gain traction, performance comparisons – already a challenging, if not dark, art – are becoming more confounding. As always the only sound comparisons rest on cost-performance and real-world evaluations for real-world applications. While prices for the MI100 have not been publicly disclosed and Nvidia does not advertise a list price for its A100s, AMD is claiming a 1.8x to 2.1x flops-per-dollar advantage over its competitor.

Fully connected 4-GPU Infinity Fabric technology hives with the AMD Instinct MI100 GPUs

Implementing the second-generation AMD Infinity Fabric Technology, AMD says the MI100 provides ~2x the peer-to-peer peak I/O bandwidth over PCIe 4.0 with up to 340 Gbps of aggregate bandwidth per card. AMD’s bridging device (see graphic) joins four MI100 PCIe cards into a single coherent scale-up solution. In a server, the MI100 GPUs can be configured with up to two integrated quad GPU hives, each providing up to 552 Gbps of peer-to-peer I/O bandwidth, according to AMD.

“We did four cards [fully-linked] because we think that is the sweet spot for HPC deployments, this four-to-one GPU to CPU ratio,” said McCredie.

Four stacks of 8GB HBM2 memory provide 32GB HBM2 memory on each MI100 GPU. At a clock rate of 1.2 GHz, that’s 1.23 Tbps of memory bandwidth. As with the MI50, the MI100’s support for PCIe Gen 4.0 technology enables 64 Gbps peak theoretical transport data bandwidth between CPU and GPU.

AMD said it has no plans for custom mezzanine form factors with this generation – but AMD does see a role for those form factors going forward as you might expect given their exascale wins (Frontier and El Capitan). While detailed node structures have not been publicly disclosed, both of these designs employ a four-to-one GPU to CPU ratio.

Source: AMD Financial Analyst Day slide (March 2020) – link to coverage

HPC market watcher Addison Snell, CEO of Intersect360 Research, remarked on AMD’s HPC focus and the implementation of its datacenter-centric CDNA architecture, distinct from the gaming-oriented RDNA (Radeon DNA) architecture.

“With the MI100 GPU, AMD is staying pure to its corporate focus on HPC,” said Snell. “While Nvidia’s messaging and benchmarking have been AI-heavy, AMD is hitting HPC hard, with 11.5 teraflops of double-precision performance as the marquee stat.”

“AMD is also emphasizing its new CDNA architecture as the focus for computing versus graphics; that’s where we find the GPU-to-GPU communication on the second-generation Infinity architecture.”

Prominent HPC sites Oak Ridge National Laboratory, the University of Pittsburgh and Pawsey Supercomputing Center evaluated the new GPUs along with AMD’s software frameworks. Their reports are positive.

“We’ve received early access to the MI100 accelerator, and the preliminary results are very encouraging. We’ve typically seen significant performance boosts, up to 2-3x compared to other GPUs,” said Bronson Messer, director of science, Oak Ridge Leadership Computing Facility. “What’s also important to recognize is the impact software has on performance. The fact that the ROCm open software platform and HIP developer tool are open source and work on a variety of platforms, it is something that we have been absolutely almost obsessed with since we fielded the very first hybrid CPU/GPU system.”

Oak Ridge National Laboratory: NAMD 2.14, STMV 1.06M atoms benchmark, 2x EPYC 7742 + MI100 vs 2x Power9 + V100 SXM, Cholla, Total Run measured. 2x EPYC 7742 + MI100 vs 2x EPYC 7742 + V100, PIConGPU, Total Run measured. 2x EPYC 7742 + MI100 vs 2x EPYC 7742 + V100, GESTS, Total Run measured, 2x EPYC 7742 + MI100 vs 2x EPYC 7742 + V100 (Source: Oak Ridge and AMD)

AMD is preparing ROCm – its open source toolset consisting of compilers, programming APIs and libraries – to be foundational for exascale computing. The recently released ROCm 4.0 has upgraded the compiler to be open source and unified to support both OpenMP 5.0 and HIP, said AMD. HIP (AMD’s heterogeneous-compute interface for portability) is a C++ runtime API that allows developers to write single-source code that can run on AMD and Nvidia GPUs (and possibly future Intel ones as well).

AMD reported that MI100-based systems will start shipping this month from a number of partners, among them Dell, Gigabyte, Hewlett Packard Enterprise and Supermicro.


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!

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, and this day of contemplation is meant to provide all of us Read more…

Intel Announces Hala Point – World’s Largest Neuromorphic System for Sustainable AI

April 22, 2024

As we find ourselves on the brink of a technological revolution, the need for efficient and sustainable computing solutions has never been more critical.  A computer system that can mimic the way humans process and s Read more…

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…

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, 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…

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…


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


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…

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…

Intel’s Xeon General Manager Talks about Server Chips 

January 2, 2024

Intel is talking data-center growth and is done digging graves for its dead enterprise products, including GPUs, storage, and networking products, which fell to Read more…

  • arrow
  • Click Here for More Headlines
  • arrow