NVIDIA Debuts PCIe-based P100; Broadens Aim at CPU Dominance

By John Russell

June 19, 2016

NVIDIA seems to be mounting a vigorous effort to dethrone the CPU as the leader of the processor pack for HPC and demanding datacenter workloads. That’s a tall order. Introduction at ISC 2016 of a PCIe-based version of is new Tesla P100 card is one element in the strategy. It should ease the upgrade path for many. But really, NVIDIA’s mantra has been shifting since introduction of the Pascal chip and DGX-1 platform last April. NVIDIA argues that better performance scaling on GPUs (Intel would dispute this), the mainstreaming of AI/deep learning approaches in scientific computing, and the large base of CUDA developers and code are combining to lift GPUs from a supportive to preeminent role.

“If you look at real applications, they tend not to scale well as you add CPU only nodes,” argues Marc Hamilton, vice president, solutions architecture and engineering at NVIDIA, citing benchmark data for Amber (molecular dynamics) running on Comet at the San Diego Supercomputing Center. “After 30 or 40 CPUs, no matter how many CPUs you add the curve doesn’t scale. Both of these charts argue for having a having a faster GPU and a more powerful compute node.” (See slide below.)

GPUs (and acceleration generally) have been transforming HPC for some time. Now the paradigm is shifting in the datacenter as well, says Hamilton who notes pointedly, “The new P100 PCIe card is targeting general purpose high performance computing. Our second ISC theme is AI is next big thing for HPC. There’s no disputing that from the consumer web side for apps [and] they use GPUs for network training. [Moreover] every major supercomputing center of the past six months is really using AI to address scientific computing that just couldn’t be addressed before.”

NVIDIA.ISC16.CPU Inefficiencies

Specs for the new Tesla P100 GPU accelerator for PCIe include:

  • 4.7 teraflops double-precision performance, 9.3 teraflops single-precision performance and 18.7 teraflops half-precision performance with NVIDIA GPU Boost technology.
  • Support for PCIe Gen 3 interconnect (32GB/sec bi-directional bandwidth).
  • Enhanced programmability with Page Migration Engine and unified memory.
  • ECC protection for increased reliability.
  • Server-optimized for highest data center throughput and reliability.
  • Available in two configurations: 16GB of CoWoS HBM2 stacked memory, delivering 720GB/sec of memory bandwidth; 12GB of CoWoS HBM2 stacked memory, delivering 540GB/sec of memory bandwidth.

“P100 for PCIe-based servers is basically the same as the NVLink-based P100 card but packaged in a standard PCIe form with a standard PCIe power footprint (300w for NVLink version versus 250w for PCIe),” reports Hamilton. “It is the same chip, the same module. We still use the HBM2 memory, same size memory, 16G, full 720GBS bandwidth to the GPU, and it has support for the page migration engine.”

Hamilton says a single Tesla P100-powered server delivers higher performance than 50 CPU-only server nodes when running the AMBER molecular dynamics code, and is faster than 32 CPU-only nodes when running the VASP material science application. Later this year, Tesla P100 accelerators for PCIe will power an upgraded version of Europe’s fastest supercomputer, the Piz Daint system at the Swiss National Supercomputing Center in Lugano, Switzerland (see Europe’s Fastest Computer to Get Pascal GPU Upgrade).

NVIDIA.ISC16.DL

Just as interesting as the P100 cards is the DGX-1 system marketed as the world’s first GPU-based deep learning supercomputer. Hamilton says NVIDIA has customers buying multiple units and that bundled DGX-1 clusters would quickly crack the TOP500 list.

When first launched, “We weren’t shipping [but] did the math for the ISC list expectations and estimated with 10-to-12 DGX-1s in a single rack you could probably get on the TOP500 list. We always simulate out what our expectations are for the new lists and for November we think on the order of 15-16 DGX-1 boxes should get you on the TOP500 list and we certainly have customers that are looking at deployment of that size and larger,” Hamilton said.

Perhaps we’ll see the emergence of a new TOP500 ‘entrant profile’ that is GPU-only or GPU-mostly. Roughly 100 of the TOP500 are accelerator-assisted machines, most by NVIDIA GPUs.

Hamilton emphasizes NVIDIA sees a broad opportunity for more pervasive penetration by GPU-only/mostly systems throughout the enterprise, especially as deep learning computing techniques are applied to a wider swath of scientific and enterprise workloads. Big Internet service providers, of course, make heavy use of GPU uses for deep learning et al. “Deep learning is a new style of computing and requires boxes like the DGX-1. We’ve seen continued interest from not only the likes of HPE, Dell, IBM, and Cray on NVLink-based designs but also from smaller OEMs as well,” says Hamilton. The latter, presumably, would more be inclined to use new P100 PCIe card.

Critics say GPU systems are more expensive. Hamilton agrees, if the metric is simply server hardware cost. “I think there’s some misconceptions about GPU systems. Of course a CPU server is more expensive because you start with a regular server and add a GPU. However the GPU-enabled datacenter running the same workload is going to be lower cost because not only do you have fewer nodes, but also you reduce all the other infrastructure at a typical supercomputer center. Turns out only 39 percent of the compute budget is used for servers; the rest of it is racking, cabling, networking, power and cooling, etc. One of the goals we’re trying to do is address that 61 percent of the budget,” he says.

The market will eventually decide, as always, but NVIDIA seems to be carefully lining up multiple arguments for its case – not least the need. NVIDIA notes that NSF was oversubscribed by 200 billion core hours, meaning rejected cycles, because its capacity was full and that capacity is heavily CPU-based.

“Accelerated computing is the only path forward to keep up with researchers’ insatiable demand for HPC and AI supercomputing,” said Ian Buck, vice president of accelerated computing at NVIDIA in the company’s official release announcement. “Deploying CPU-only systems to meet this demand would require large numbers of commodity compute nodes, leading to substantially increased costs without proportional performance gains. Dramatically scaling performance with fewer, more powerful Tesla P100-powered nodes puts more dollars into computing instead of vast infrastructure overhead.”

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!

Energy Exascale Earth System Model Version 2 Promises Twice the Speed

October 18, 2021

The Energy Exascale Earth System Model (E3SM) is an ongoing Department of Energy (DOE) earth system modeling, simulation and prediction project aiming to “assert and maintain an international scientific leadership posi Read more…

Intel Reorgs HPC Group, Creates Two ‘Super Compute’ Groups

October 15, 2021

Following on changes made in June that moved Intel’s HPC unit out of the Data Platform Group and into the newly created Accelerated Computing Systems and Graphics (AXG) business unit, led by Raja Koduri, Intel is making further updates to the HPC group and announcing... Read more…

Royalty-free stock illustration ID: 1938746143

MosaicML, Led by Naveen Rao, Comes Out of Stealth Aiming to Ease Model Training

October 15, 2021

With more and more enterprises turning to AI for a myriad of tasks, companies quickly find out that training AI models is expensive, difficult and time-consuming. Finding a new approach to deal with those cascading challenges is the aim of a new startup, MosaicML, that just came out of stealth... Read more…

NSF Awards $11M to SDSC, MIT and Univ. of Oregon to Secure the Internet

October 14, 2021

From a security standpoint, the internet is a problem. The infrastructure developed decades ago has cracked, leaked and been patched up innumerable times, leaving vulnerabilities that are difficult to address due to cost Read more…

SC21 Announces Science and Beyond Plenary: the Intersection of Ethics and HPC

October 13, 2021

The Intersection of Ethics and HPC will be the guiding topic of SC21's Science & Beyond plenary, inspired by the event tagline of the same name. The evening event will be moderated by Daniel Reed with panelists Crist Read more…

AWS Solution Channel

Cost optimizing Ansys LS-Dyna on AWS

Organizations migrate their high performance computing (HPC) workloads from on-premises infrastructure to Amazon Web Services (AWS) for advantages such as high availability, elastic capacity, latest processors, storage, and networking technologies; Read more…

Quantum Workforce – NSTC Report Highlights Need for International Talent

October 13, 2021

Attracting and training the needed quantum workforce to fuel the ongoing quantum information sciences (QIS) revolution is a hot topic these days. Last week, the U.S. National Science and Technology Council issued a report – The Role of International Talent in Quantum Information Science... Read more…

Intel Reorgs HPC Group, Creates Two ‘Super Compute’ Groups

October 15, 2021

Following on changes made in June that moved Intel’s HPC unit out of the Data Platform Group and into the newly created Accelerated Computing Systems and Graphics (AXG) business unit, led by Raja Koduri, Intel is making further updates to the HPC group and announcing... Read more…

Royalty-free stock illustration ID: 1938746143

MosaicML, Led by Naveen Rao, Comes Out of Stealth Aiming to Ease Model Training

October 15, 2021

With more and more enterprises turning to AI for a myriad of tasks, companies quickly find out that training AI models is expensive, difficult and time-consuming. Finding a new approach to deal with those cascading challenges is the aim of a new startup, MosaicML, that just came out of stealth... Read more…

Quantum Workforce – NSTC Report Highlights Need for International Talent

October 13, 2021

Attracting and training the needed quantum workforce to fuel the ongoing quantum information sciences (QIS) revolution is a hot topic these days. Last week, the U.S. National Science and Technology Council issued a report – The Role of International Talent in Quantum Information Science... Read more…

Eni Returns to HPE for ‘HPC4’ Refresh via GreenLake

October 13, 2021

Italian energy company Eni is upgrading its HPC4 system with new gear from HPE that will be installed in Eni’s Green Data Center in Ferrera Erbognone (a provi Read more…

The Blueprint for the National Strategic Computing Reserve

October 12, 2021

Over the last year, the HPC community has been buzzing with the possibility of a National Strategic Computing Reserve (NSCR). An in-utero brainchild of the COVID-19 High-Performance Computing Consortium, an NSCR would serve as a Merchant Marine for urgent computing... Read more…

UCLA Researchers Report Largest Chiplet Design and Early Prototyping

October 12, 2021

What’s the best path forward for large-scale chip/system integration? Good question. Cerebras has set a high bar with its wafer scale engine 2 (WSE-2); it has 2.6 trillion transistors, including 850,000 cores, and was fabricated using TSMC’s 7nm process on a roughly 8” x 8” silicon footprint. Read more…

What’s Next for EuroHPC: an Interview with EuroHPC Exec. Dir. Anders Dam Jensen

October 7, 2021

One year after taking the post as executive director of the EuroHPC JU, Anders Dam Jensen reviews the project's accomplishments and details what's ahead as EuroHPC's operating period has now been extended out to the year 2027. Read more…

University of Bath Unveils Janus, an Azure-Based Cloud HPC Environment

October 6, 2021

The University of Bath is upgrading its HPC infrastructure, which it says “supports a growing and wide range of research activities across the University.” Read more…

Ahead of ‘Dojo,’ Tesla Reveals Its Massive Precursor Supercomputer

June 22, 2021

In spring 2019, Tesla made cryptic reference to a project called Dojo, a “super-powerful training computer” for video data processing. Then, in summer 2020, Tesla CEO Elon Musk tweeted: “Tesla is developing a [neural network] training computer... Read more…

Enter Dojo: Tesla Reveals Design for Modular Supercomputer & D1 Chip

August 20, 2021

Two months ago, Tesla revealed a massive GPU cluster that it said was “roughly the number five supercomputer in the world,” and which was just a precursor to Tesla’s real supercomputing moonshot: the long-rumored, little-detailed Dojo system. Read more…

Esperanto, Silicon in Hand, Champions the Efficiency of Its 1,092-Core RISC-V Chip

August 27, 2021

Esperanto Technologies made waves last December when it announced ET-SoC-1, a new RISC-V-based chip aimed at machine learning that packed nearly 1,100 cores onto a package small enough to fit six times over on a single PCIe card. Now, Esperanto is back, silicon in-hand and taking aim... Read more…

CentOS Replacement Rocky Linux Is Now in GA and Under Independent Control

June 21, 2021

The Rocky Enterprise Software Foundation (RESF) is announcing the general availability of Rocky Linux, release 8.4, designed as a drop-in replacement for the soon-to-be discontinued CentOS. The GA release is launching six-and-a-half months... Read more…

US Closes in on Exascale: Frontier Installation Is Underway

September 29, 2021

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, held by Zoom this week (Sept. 29-30), it was revealed that the Frontier supercomputer is currently being installed at Oak Ridge National Laboratory in Oak Ridge, Tenn. The staff at the Oak Ridge Leadership... Read more…

Intel Completes LLVM Adoption; Will End Updates to Classic C/C++ Compilers in Future

August 10, 2021

Intel reported in a blog this week that its adoption of the open source LLVM architecture for Intel’s C/C++ compiler is complete. The transition is part of In Read more…

Intel Reorgs HPC Group, Creates Two ‘Super Compute’ Groups

October 15, 2021

Following on changes made in June that moved Intel’s HPC unit out of the Data Platform Group and into the newly created Accelerated Computing Systems and Graphics (AXG) business unit, led by Raja Koduri, Intel is making further updates to the HPC group and announcing... Read more…

Hot Chips: Here Come the DPUs and IPUs from Arm, Nvidia and Intel

August 25, 2021

The emergence of data processing units (DPU) and infrastructure processing units (IPU) as potentially important pieces in cloud and datacenter architectures was Read more…

Leading Solution Providers

Contributors

AMD-Xilinx Deal Gains UK, EU Approvals — China’s Decision Still Pending

July 1, 2021

AMD’s planned acquisition of FPGA maker Xilinx is now in the hands of Chinese regulators after needed antitrust approvals for the $35 billion deal were receiv Read more…

HPE Wins $2B GreenLake HPC-as-a-Service Deal with NSA

September 1, 2021

In the heated, oft-contentious, government IT space, HPE has won a massive $2 billion contract to provide HPC and AI services to the United States’ National Security Agency (NSA). Following on the heels of the now-canceled $10 billion JEDI contract (reissued as JWCC) and a $10 billion... Read more…

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

Quantum Roundup: IBM, Rigetti, Phasecraft, Oxford QC, China, and More

July 13, 2021

IBM yesterday announced a proof for a quantum ML algorithm. A week ago, it unveiled a new topology for its quantum processors. Last Friday, the Technical Univer Read more…

The Latest MLPerf Inference Results: Nvidia GPUs Hold Sway but Here Come CPUs and Intel

September 22, 2021

The latest round of MLPerf inference benchmark (v 1.1) results was released today and Nvidia again dominated, sweeping the top spots in the closed (apples-to-ap Read more…

Frontier to Meet 20MW Exascale Power Target Set by DARPA in 2008

July 14, 2021

After more than a decade of planning, the United States’ first exascale computer, Frontier, is set to arrive at Oak Ridge National Laboratory (ORNL) later this year. Crossing this “1,000x” horizon required overcoming four major challenges: power demand, reliability, extreme parallelism and data movement. Read more…

Intel Unveils New Node Names; Sapphire Rapids Is Now an ‘Intel 7’ CPU

July 27, 2021

What's a preeminent chip company to do when its process node technology lags the competition by (roughly) one generation, but outmoded naming conventions make i Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire