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AMD EPYC : Four Supercomputers In Top 50, Ten In Top 500!

AMD EPYC : Four Supercomputers In Top 50, Ten In Top 500!

AMD is on the roll, announcing more supercomputing wins for their 2nd Gen EPYC processors, including four supercomputers in the top 50 list, and ten in the top 500!

 

2nd Gen AMD EPYC : A Quick Primer

The 2nd Gen AMD EPYC family of server processors are based on the AMD Zen 2 microarchitecture and fabricated on the latest 7 nm process technology.

According to AMD, they offer up to 90% better integer performance and up to 79% better floating-point performance, than the competing Intel Xeon Platinum 8280 processor. For more details :

Here is a quick 7.5 minute summary of the 2nd Gen EPYC product presentations by Dr. Lisa Su, Mark Papermaster and Forrest Norrod!

 

AMD EPYC : Four Supercomputers In Top 50, Ten In Top 500!

Thanks to the greatly improved performance of their 2nd Gen EPYC processors, they now power four supercomputers in the top 50 list :

Top 50 Rank Supercomputer Processor
7 Selene
NVIDIA DGX A100 SuperPOD
AMD EPYC 7742
30 Belenos
Atos BullSequana XH2000
AMD EPYC 7H12
34 Joilot-Curie
Atos BullSequana XH2000
AMD EPYC 7H12
48 Mahti
Atos BullSequana XH2000
AMD EPYC 7H12

On top of those four supercomputers, there are another six other supercomputers in the Top 500 ranking, powered by AMD EPYC.

In addition to powering supercomputers, AMD EPYC 7742 processors will soon power Gigabyte servers selected by CERN to handle data from their Large Hadron Collider (LHC).

 

3rd Gen AMD EPYC Supercomputers

AMD also announced that two universities will deploy Dell EMC PowerEdge servers powered by the upcoming 3rd Gen AMD EPYC processors.

Indiana University

Indiana University will deploy Jetstream 2 – an eight-petaflop distributed cloud computing system, powered by the upcoming 3rd Gen AMD EPYC processors.

Jetstream 2 will be used by researchers in a variety of fields like AI, social sciences and COVID-19 research.

Purdue University

Purdue University will deploy Anvil – a supercomputer powered by the upcoming 3rd Gen AMD EPYC processors, for use in a wide range of computational and data-intensive research.

AMD EPYC will also power Purdue University’s community cluster “Bell”, scheduled for deployment in the fall.

 

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AMD Datacenter Leadership In 2020 & Beyond!

AMD Senior VP and General Manager Forrest Norrod just shared AMD’s datacenter leadership with EPYC and Radeon Instinct, and AMD’s datacenter roadmap beyond 2020!

 

Forrest Norrod : Senior VP + GM, AMD Datacenter + Embedded Solutions Business Group

Forrest Norrod is senior vice president and general manager of the Datacenter and Embedded Solutions Business Group at AMD.

He is responsible for managing all aspects of strategy, business management, engineering and sales for AMD datacenter and embedded products.

Norrod has more than 25 years of technology industry experience across a number of engineering and business management roles at both the chip and system level.

 

AMD Datacenter Leadership In 2020 & Beyond!

During AMD Financial Analyst Day 2020, Forrest Norrod shared AMD’s datacenter leadership with EPYC and Radeon Instinct, and AMD’s datancenter roadmap in this presentation.

Here are the key points from Forrest Norrod’s presentation :

  • AMD won the contract to power the recently announced El Capitan supercomputer at Lawrence Livermore National Laboratory with EPYC processors and Radeon Instinct GPUs.
  • Expected to come online in 2023, El Capitan is expected to deliver more than 2 exaFLOPs of double-precision performance, making it more powerful than today’s 200 fastest supercomputers combined.

  • AMD is continuing to gain traction with its 2nd Generation AMD EPYC processors in enterprise, cloud and HPC markets based on delivering performance leadership and TCO advantages across the most important enterprise and cloud workloads.
  • AMD EPYC is enabling Nokia to double the performance of their 5G Cloud Packet Core.
  • In 2020 AMD expects more than 150 AMD EPYC processor-powered cloud instances and 140 server platforms to be available.

  • AMD is introducing new technologies including AMD CDNA architecture, 3rd Generation Infinity Architecture and the ROCm 4.0 software platform, all of which will support the AMD-powered Frontier and El Capitan supercomputers.
  • AMD plans to ship the 3rd Gen AMD EPYC “Milan” processor in Late 2020, and it will provide 100% coverage of enterprise requirements – whether it’s for the cloud, HPC or enterprise IT.
  • Milan will remain on the 7 nm process, but the next-generation Genda core (Zen 4) will use the 5 nm process technology.

  • The AMD CDNA architecture will allow for better scalability, with accelerators fully interconnected with 2nd Gen Infinity Architecture.
  • But the next-generation AMD CDNA 2 architecture will allow for Unified Data, with CPU + GPU coherency with 3rd Gen Infinity Architecture – allowing for easier programming and improved performance.

 

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El Capitan Supercomputer : AMD Selected As Node Supplier!

It’s official – AMD has been selected as the node supplier for the El Capitan supercomputer, which is projected to be the world’s most powerful supercomputer when it is fully deployed!

 

El Capitan Supercomputer : A Quick Primer!

El Capitan is a supercomputer funded by the Advanced Simulation and Computing (ASC) program at the National Nuclear Security Administration (NNSA) from the Department of Energy.

When it is fully deployed in 2023, it will perform complex and increasingly predictive modelling and simulation for the NNSA’s Life Extension Programs (LEPs), which addresses nuclear weapon raging and emergent threat issues.

This will allow the United States to keep its nuclear stockpile safe, secure and reliable, in the absence of underground nuclear testing.

“This unprecedented computing capability, powered by advanced CPU and GPU technology from AMD, will sustain America’s position on the global stage in high-performance computing and provide an observable example of the commitment of the country to maintaining an unparalleled nuclear deterrent,” said LLNL Director Bill Goldstein.

“Today’s news provides a prime example of how government and industry can work together for the benefit of the entire nation.”

Besides supporting the nuclear stockpile, El Capitan will perform secondary US national security missions, including nuclear nonproliferation and counterterrorism.

NNSA laboratories – Lawrence Livermore, Los Alamos and Sandia national laboratories – are building machine learning and AI into computational techniques and analysis that will benefit NNSA’s primary missions and unclassified projects such as climate modelling and cancer research for DOE.

To that end, it will use a combination of CPUs and GPUs to exceed 2 exaFLOPS in performance – that’s two quintillion floating point operations per second. That will make it the world’s most powerful supercomputer!

 

El Capitan Supercomputer : AMD Selected As Node Supplier!

El Capitan will be powered by the next-generation AMD EPYC processors, codenamed Genoa and featuring the upcoming AMD Zen 4 processor cores, as well as the next-generation AMD Radeon Instinct GPUs based on a new compute-optimised architecture.

The nodes will run on the AMD Radeon Open Compute (ROCm) heterogenous computing platform, with most of their floating point computing power delivered by the Radeon Instinct GPUs.

Not only will the El Capitan nodes offer significantly greater per-node performance than any current system, they will also offer dramatically better energy efficiency.

El Capitan will also integrated advanced features that have not yet been widely deployed, including :

  • HPE Cray Slingshot interconnect network, which will enable large calculations across many nodes
  • new HPE optics technologies to deliver higher data transmission rates with better power efficiency and reliability
  • new Cray Shasta software platform, with a new container-based architecture

“El Capitan will drive unprecedented advancements in HPC and AI, powered by the next-generation AMD EPYC CPUs and Radeon Instinct GPUs,” said Forrest Norrod, senior vice president and general manager, Datacenter and Embedded Systems Group, AMD.

“Building on our strong foundation in high-performance computing and adding transformative coherency capabilities, AMD is enabling the NNSA Tri-Lab community — LLNL, Los Alamos and Sandia national laboratories — to achieve their mission-critical objectives and contribute new AI advancements to the industry.”

“We are extremely proud to continue our exascale work with HPE and NNSA and look forward to the delivery of the most powerful supercomputer in the world, expected in early 2023.”

 

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NVIDIA DRIVE PX 2 : First AI Supercomputer For Cars

Special by Danny Shapiro, NVIDIA

Take a supercomputer. Give it wheels. The result: a robot that can take you anywhere you want to go. No wonder self-driving cars were the hot topic at CES last week, and the talk of the Detroit Auto Show this week.

Building this new generation of super-smart cars requires some serious intelligence. That’s why we introduced NVIDIA DRIVE PX 2, our artificial intelligence supercomputer for the car. We’re taking the GPU technology at the heart of a revolution that’s giving computers superhuman powers of perception and putting it in your driveway.

Here’s why your next car might be your first supercomputer:

 

NVIDIA DRIVE PX 2 : First AI Supercomputer For Cars

Only next generation AI has the adaptability, and the power, to understand what cars encounter on the road.

There aren’t enough engineers in Silicon Valley to hand-code software that can account for everything that happens when you drive. To deal with all the stuff a car sees on the road – and thanks to modern sensors, they see more and more – you need deep learning, a form of artificial intelligence. Last year, GPU-powered deep learning systems exceeded human levels of perception for the first time.

 

Our GPUs Make AI Practical

GPUs are built for parallel computing. So they’re ideal for deep neural networks – complex mathematical models that mimic the brain. DNNs are trained by feeding massive amounts of data into powerful computers. Parallel computing is the only practical way to digest this info rapidly. And DNNs are ideal for driving, because the more data you give them, the smarter they get.

 

NVIDIA DRIVE PX 2 Brings AI to the Road

NVIDIA DRIVE PX 2 can perform 24 trillion deep learning operations per second, and it has the processing power of 150 MacBook Pros. It lets developers to replace the trunk full of GPU-based workstations in their vehicles with a supercomputer the size of a lunchbox.

 

We Built DRIVE PX 2 to be a Scalable Platform for Car Companies

We designed DRIVE PX 2 to handle everything from advanced driver assistance systems to fully self-driving vehicles. It can be configured as a single-processor, air-cooled system for driver assistance, up to a four-processor, liquid-cooled system for autonomous driving. Whatever the case, it’s based on one scalable Architecture – the same that powers the world’s most advanced supercomputers.

 

DRIVE PX 2 Is An Open Platform

NVIDIA DRIVE PX 2 is built with the same open, programmable GPU architecture that’s driving an AI revolution. Audi, BMW, Ford, Mercedes and ZMP (makers of the RoboTaxi) are already using our AI platform for their autonomous car R&D.

Our open, programmable platform is being used by More than 50 automakers, Tier 1 suppliers, software companies and startups are using NVIDIA DRIVE PX to develop deep neural networks.

 

Car Companies Can Make Their Cars Safer Every Day

GPUs have already accelerated the training of deep neural networks by 20 to 30 times. What used to take months to train, now takes just days. This lets us create a brain for autonomous vehicles that is always alert, and can achieve superhuman levels of situational awareness.  The more data these cars scoop up and share with one another, the smarter they all get.

 

AI-Equipped Cars Are Coming Soon

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Earlier this month, Volvo announced it selected NVIDIA DRIVE PX 2 to power its fleet of autonomous cars. They’re outfitting their award-winning XC90 SUV with it – and will let drivers put these cars into autonomous driving mode on public roads around its hometown of Gothenburg, Sweden.

 

Everyone’s Investing in Automotive Supercomputing

GM has invested $500 million with Lyft on self-driving technologies. Toyota recently earmarked $1 billion for AI research. Just yesterday, the U.S. government put forth a $4 billion investment plan in support of autonomous driving technologies and the infrastructure to enable it.

This is just the start. Our goal is to make this technology available across all vehicle types and segments.  Putting supercomputers on wheels is going to reduce the number accidents, injuries and fatalities. It’s going to make new capabilities – and new kinds of transportation – possible.

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