Dell to Build 10-Petaflop Supercomputer For Science

By Michael Feldman

September 22, 2011

The Texas Advanced Computing Center (TACC) has revealed plans to deploy a cutting-edge petascale supercomputer courtesy of a $27.5 million dollar NSF award. Built by Dell, the system will consist of 2 petaflops of Sandy Bridge-EP processors with an 8 petaflop boost from Intel’s Many Integrated Core (MIC) coprocessors. The machine is scheduled to boot up in late 2012 and be ready for production in January 2013.

Not only is this Dell’s first petascale system — at least the first one announced publicly — it will likely be the first deployment of Intel’s commercial MIC technology. In this case, the chips in question are pre-production versions of Knights Corner, the first commercial part in that product line. These early chips will be identical to the future production parts.

Stampede, as the system will be called, is meant to serve both traditional number crunching HPC applications and data-driven analytics applications within NSF’s eXtreme Digital (XD) user community. XD includes the Extreme Science and Engineering Discovery Environment (XSEDE) project, the sucessor to TeraGrid that encompasses more than a dozen universities and two research labs. At 10 teraflops, Stampede will be the most powerful resource for XD users.

According to Jay Boisseau, TACC Director and PI of the Stampede project, the system is expected to have several hundred projects running on it from day one. “We want to bring in users with big data sets that are doing large-scale analyses, as well as the simulations types of users,” he told HPCwire.

Data-intensive science applications include traditional ones like bioinformatics, but also codes from geosciences and astronomy — application domains that are already accumulating large amounts of digital data. Boisseau thinks as much as half of Stampede’s resources will be devoted to these types of applications.

The data-intensive support will bring in a new set of users, many of which are not as HPC savvy as the traditional simulations folks. For that, Boisseau is planning to develop a much richer software environment for this group, including new application portals and gateways, as was begun under the TeraGrid project. In addition, they will also look to bring in experts in statistics, data mining, data management, and so on, in order to support the data-driven application domain.

Some of the expertise and software resources are already built into the project via university collaborations. Besides The University of Texas at Austin, partner schools include Clemson University, University of Colorado at Boulder, Cornell University, Indiana University, Ohio State University, and The University of Texas at El Paso.

Hardware-wise, the foundation of Stampede is a 2 petaflop cluster with 6,400 x86 compute nodes, lashed together with FDR (56 Gbps) InfiniBand from Mellanox. Each node will house two of Intel’s 8-core Xeon E5 (aka Sandy Bridge-EP) and 32 GB of DRAM.

Stampede will also include 16 big memory nodes, each sporting 1 terabyte of DRAM and 2 NVIDIA GPUs. Memory-wise, that’s not exactly in SGI Altix UV territory, but it’s a respectable capacity for extra-large SMP applications. Boisseau says they’re also considering ScaleMP’s virtual SMP solution to construct a shared memory environment across all 16 TB. The shared memory sub-cluster is slated to be used for some of the big data analytics applications that Stampede will host.

The cluster will also be hooked up to to Lustre storage nodes, also suppled by Dell. It will consist of 14 PB of disk, and deliver an aggregated bandwidth of 150 GB/second. “Over the lifetime of the project we’re expecting that to grow substantially both in capacity and bandwidth over the lifetime of the system,” said Boisseau.

The Dell system was developed by its Data Center Solutions division, under the code-name Zeus. Although the technology will debut in Stampede, the company is expecting to make the Zeus product generally available for “hyperscale” supercomputing in 2012.

Stampede’s base cluster and storage nodes represent the lion’s share of the NSF funding at $25 million. The remaining $2.5 million will go toward 8 petaflops worth of MIC coprocessors, which will be hooked into the x86 nodes via PCIe 3.0 links. MIC is Intel’s x86-based manycore HPC architecture aimed at highly parallel codes, and competes head on with NVIDIA’s Tesla and AMD’s Firestream GPUS.

GPGPU enthusiasts were not completely slighted though. Besides the GPUs in the shared memory nodes, 128 of the 6,400 regular nodes will be outfitted with NVIDIA’s next-generation Kepler GPUs to support remote visualization. Kepler is the successor to Fermi, NVIDIA’s current GPU architecture. Tesla implementations of Kepler aimed at HPC servers should begin shipping sometime in 2012.

Intel has not announced an official launch date for the Knights Corner MIC product, but it should be generally available sometime in 2013, or perhaps late 2012 if Intel’s 22nm process technology ramps up more quickly. The actual number of MICs in Stampede is not public, but Intel has promised them enough to deliver 8 peak petaflops.

Using a little quick math, each MIC chip will probably need to deliver at least 1.3 to 1.5 double precision teraflops to hit the 8 petaflop performance target. Coincidentally, the NVIDIA’s Kepler GPU is also expected to deliver about 1.3 to 1.5 double precision teraflops. Note that the first MIC parts will be implemented with Intel’s Tri-Gate 22nm technology, while the Kepler GPUs will be manufactured on standard 28nm technology.

At this point, Boisseau is expecting to receive all the Intel MIC coprocessors sometime this fall, possibly in time for a Linpack run at the November’s TOP500. By that time, all the Sandy Bridge compute nodes should be fully deployed. If all goes according to plan, early access users should be able to start running codes on the machine by December 2012.

Although MIC will support a number of parallel computing models, the most straightforward one is OpenMP. This will be especially advantageous for users with hybrid MPI-OpenMP codes. The idea would be to just offload the OpenMP chunks to the coprocessors in order to parallelize those loops. Users with straight MPI codes will need to do more work to tap into MIC acceleration.

There is already an upgraded version of Stampede on the drawing board. About two years into the project, TACC is planning to deploy the second generation MIC coprocessors, with another (smaller) batch of chips. The goal is to add 5 more petaflops to the system, bringing its grand total to 15 peak petaflops sometime around the middle of the decade.

The NSF is will be funding Stampede for at least four years. Besides the inital $27.5 million outlay to build and install the system, an additional $24 million or so for system operation and support is expected to be on the table soon, bringing the total Stampede investment to more than $50 million. The project also includes an option for renewal in 2017, which would result in the deployment of an even larger and more powerful machine toward the end of the decade.

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!

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…

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 pressing needs and hurdles to widespread AI adoption. The sudde Read more…

Quantinuum Reports 99.9% 2-Qubit Gate Fidelity, Caps Eventful 2 Months

April 16, 2024

March and April have been good months for Quantinuum, which today released a blog announcing the ion trap quantum computer specialist has achieved a 99.9% (three nines) two-qubit gate fidelity on its H1 system. The lates Read more…

Mystery Solved: Intel’s Former HPC Chief Now Running Software Engineering Group 

April 15, 2024

Last year, Jeff McVeigh, Intel's readily available leader of the high-performance computing group, suddenly went silent, with no interviews granted or appearances at press conferences.  It led to questions -- what's 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 Institute for Human-Centered AI (HAI) put out a yearly report to t Read more…

Crossing the Quantum Threshold: The Path to 10,000 Qubits

April 15, 2024

Editor’s Note: Why do qubit count and quality matter? What’s the difference between physical qubits and logical qubits? Quantum computer vendors toss these terms and numbers around as indicators of the strengths of t 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…

Computational Chemistry Needs To Be Sustainable, Too

April 8, 2024

A diverse group of computational chemists is encouraging the research community to embrace a sustainable software ecosystem. That's the message behind a recent Read more…

Hyperion Research: Eleven HPC Predictions for 2024

April 4, 2024

HPCwire is happy to announce a new series with Hyperion Research  - a fact-based market research firm focusing on the HPC market. In addition to providing mark 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…

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…

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…

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
HPCwire