Lawrence Livermore Builds Stable of Workhorse Clusters

By Michael Feldman

September 23, 2009

After the 1992 moratorium on underground testing of nuclear weapons in the US went into effect, the Department of Energy’s National Nuclear Security Administration’s (NNSA) was tasked to maintain the country’s nuclear weapon deterrent via computing simulations. As a result, Lawrence Livermore National Laboratory (LLNL) and its two sister labs at Los Alamos and Sandia became the recipients of some of the most muscular computing hardware in the world. Today these institutions are at the forefront of supercomputing expertise, both hardware and software.

Because the weapons simulation applications are always looking to achieve higher resolution, higher fidelity, and full-system modeling, there is an ongoing demand for ever-more powerful capability-class supercomputers. Today, Los Alamos houses what is ostensibly the world’s most powerful computer — Roadrunner — which clocks in at over a petaflop. In a couple of years, LLNL is slated to deploy “Sequoia,” a 20-petaflop IBM Blue Gene/Q machine, and a likely contender for the top supercomputer in 2011. Sequoia’s predecessor, “Dawn,” is a 500 teraflop Blue Gene/P machine installed earlier this year at Livermore.

But according to Mike McCoy, who heads Livermore’s Scientific Computing and Communications Department, it’s not all about these elite capability machines. He says 10 to 30 percent of the computational resources at the lab are devoted to capacity systems, that is, commodity HPC Linux clusters. The reason is simple. There is a lot of computing to be done, and time on the expensive capability systems is dear. By necessity a lot of application work has to be developed and tested on these smaller, less expensive machines as a way to contain costs.

There is also quite a bit of unclassified science work performed at the lab in the areas of climate, biology, molecular dynamics, and energy research. Some of this basic science supports the weapons programs, but the remainder is just part of the NNSA’s larger mission of furthering national security. The unclassified work also serves to nurture the lab’s scientists, and without them, there is no weapons program. In any case, the vast majority of this class of computing takes place on vanilla Linux clusters, albeit very large ones.

Today at Livermore, capacity clusters account for 404 teraflops of computing power, while the capability machines deliver 1,324 teraflops. Another 205 teraflops are available in visualization and collaboration systems. The most powerful capability system at the facility is the half-petaflop Dawn, while the largest capacity cluster is Juno, which weighs in at 167 teraflops.

HPC machines at Lawrence Livermore National Laboratory

Livermore has relied on a number of cluster computer vendors over the years. In 2002, the now-defunct Linux Networx installed a the MCR cluster, which delivered a 7.6 teraflops, a performance level that earned it the number three spot on the TOP500 list in June 2003. A more recent vendor is Appro, who won the Peloton contract in 2006 and then the subsequent Tri-Lab Linux Capacity Cluster (TLCC) deal, which served all three NNSA labs.

Today Lawrence Livermore appears to be grooming Dell for some major deployments. Up until last year, the only Dell machines at the lab were sitting on people’s desks. But in November 2008, the company became the cluster partner on the Hyperion project, a testbed system to be used to develop system and application software for HPC. The idea was to provide a platform for developers to build and test codes at scale before they are deployed on larger production systems. That effort has produced some early results including simulating the file system and I/O rates of the future Sequoia system using Hyperion’s InfiniBand and Ethernet SANs.

Last week, Michael Dell met with LLNL officials at Livermore to get a sense of what the NNSA is expecting from its future cluster system. The agency’s goal is to maintain at least a 1:10 performance ratio between capacity systems and capability systems. Today that means you need roughly a 100 teraflop cluster to match up with the purpose-built one-petaflop supers. With Sequoia coming online in 2011, the folks at LLNL are already thinking about clusters in the two-petaflop range. Beyond that the lab see the need for 100-teraflop commodity machines in 2018, in anticipation of capability machines hitting the exaflop mark. That means vendors need to scale today’s commodity clusters by a factor of 10 over the next 9 years.

Recently Dell installed “Coastal,” an 88.5 teraflop system that is being used by the Lawrence Livermore’s National Ignition Facility to help with fusion research. Next year, with Dell’s help, the lab will be more than doubling the performance of the 90 teraflop Hyperion system with “Sierra,” a new cluster that is spec’ed to reach 220 teraflops.

Michael Dell is hoping that’s just the beginning. From his point of view, designing systems pushing the envelope of scalability and technology dovetails nicely with the company’s other big server segments, namely web services infrastructure and cloud computing. For example, the inclusion of SSD technology to increase I/O performance in the Livermore’s Coastal cluster also turned out to be a good solution for Dell servers deployed for a Web search provider in China (presumably Baidu). He sees the demand for these super-sized machines inside and outside of HPC as two sides of the same hyperscale coin. And, he says, the technology transfer travels in both directions. “You always learn from your best customers,” says Dell.

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!

Fluid HPC: How Extreme-Scale Computing Should Respond to Meltdown and Spectre

February 15, 2018

The Meltdown and Spectre vulnerabilities are proving difficult to fix, and initial experiments suggest security patches will cause significant performance penalties to HPC applications. Even as these patches are rolled o Read more…

By Pete Beckman

Intel Touts Silicon Spin Qubits for Quantum Computing

February 14, 2018

Debate around what makes a good qubit and how best to manufacture them is a sprawling topic. There are many insistent voices favoring one or another approach. Referencing a paper published today in Nature, Intel has offe Read more…

By John Russell

Brookhaven Ramps Up Computing for National Security Effort

February 14, 2018

Last week, Dan Coats, the director of Director of National Intelligence for the U.S., warned the Senate Intelligence Committee that Russia was likely to meddle in the 2018 mid-term U.S. elections, much as it stands accused of doing in the 2016 Presidential election. Read more…

By John Russell

HPE Extreme Performance Solutions

Safeguard Your HPC Environment with the World’s Most Secure Industry Standard Servers

Today’s organizations operate in an environment with ever-evolving threats, and in order to protect themselves they must continuously bolster their security strategy. Hewlett Packard Enterprise (HPE) and Intel® are addressing modern security challenges with the world’s most secure industry standard servers powered by the latest generation of Intel® Xeon® Scalable processors. Read more…

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended to make it easier, faster and cheaper to train and run machi Read more…

By Doug Black

Fluid HPC: How Extreme-Scale Computing Should Respond to Meltdown and Spectre

February 15, 2018

The Meltdown and Spectre vulnerabilities are proving difficult to fix, and initial experiments suggest security patches will cause significant performance penal Read more…

By Pete Beckman

Brookhaven Ramps Up Computing for National Security Effort

February 14, 2018

Last week, Dan Coats, the director of Director of National Intelligence for the U.S., warned the Senate Intelligence Committee that Russia was likely to meddle in the 2018 mid-term U.S. elections, much as it stands accused of doing in the 2016 Presidential election. Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

The Food Industry’s Next Journey — from Mars to Exascale

February 12, 2018

Global food producer and one of the world's leading chocolate companies Mars Inc. has a unique perspective on the impact that exascale computing will have on the food industry. Read more…

By Scott Gibson, Oak Ridge National Laboratory

Singularity HPC Container Start-Up – Sylabs – Emerges from Stealth

February 8, 2018

The driving force behind Singularity, the popular HPC container technology, is bringing the open source platform to the enterprise with the launch of a new vent Read more…

By George Leopold

Dell EMC Debuts PowerEdge Servers with AMD EPYC Chips

February 6, 2018

AMD notched another EPYC processor win today with Dell EMC’s introduction of three PowerEdge servers (R6415, R7415, and R7425) based on the EPYC 7000-series p Read more…

By John Russell

‘Next Generation’ Universe Simulation Is Most Advanced Yet

February 5, 2018

The research group that gave us the most detailed time-lapse simulation of the universe’s evolution in 2014, spanning 13.8 billion years of cosmic evolution, is back in the spotlight with an even more advanced cosmological model that is providing new insights into how black holes influence the distribution of dark matter, how heavy elements are produced and distributed, and where magnetic fields originate. Read more…

By Tiffany Trader

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he Read more…

By John Russell

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Leading Solution Providers

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released Read more…

By Tiffany Trader

V100 Good but not Great on Select Deep Learning Aps, Says Xcelerit

November 27, 2017

Wringing optimum performance from hardware to accelerate deep learning applications is a challenge that often depends on the specific application in use. A benc Read more…

By John Russell

SC17: Singularity Preps Version 3.0, Nears 1M Containers Served Daily

November 1, 2017

Just a few months ago about half a million jobs were being run daily using Singularity containers, the LBNL-founded container platform intended for HPC. That wa Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This