Sequoia Supercomputer Pumps Up Heart Research

By Tiffany Trader

October 24, 2012

Cardioid code image

The Cardioid code developed by a team of Livermore and IBM scientists divides the heart into a large number of manageable pieces, or subdomains. The development team used two approaches, called Voronoi (left) and grid (right), to break the enormous computing challenge into much smaller individual tasks. Source: LLNL

The world’s fastest computer has created the fastest computer simulation of the human heart.

The Lawrence Livermore National Laboratory’s Sequoia supercomputer, a TOP500 chart topper, was built to handle top secret nuclear weapons simulations, but before it goes behind the classified curtain, it is pumping out sophisticated cardiac simulations.

Earlier this month, Sequoia, which currently ranks number one on the TOP500 list of the world’s fastest computer systems, received a 2012 Breakthrough Award from Popular Mechanics magazine. Now the magazine is reporting on Sequoia’s ground-breaking heart simulations.

Clocking in at 16.32 sustained petaflops (20 PF peak), Sequoia is taking modeling and simulation to new heights, enabling researchers to capture greater complexity in a shorter time frame. With this advanced capability, LLNL scientists have been able to simulate the human heart down to the cellular level and use the resulting model to predict how the organ will respond to different drug compounds.

Principal investigator Dave Richards couldn’t resist a little showboating: “Other labs are working on similar models for many body systems, including the heart,” he told Popular Mechanics. “But Lawrence Livermore’s model has one major advantage: It runs on Sequoia, the most powerful supercomputer in the world and a recent PM Breakthrough Award winner.”

The simulations were made possible by an advanced modeling program, called Cardioid, that was developed by a team of scientists from LLNL and the IBM T. J. Watson Research Center. The highly scalable code simulates the electrophysiology of the heart. It works by breaking down the heart into units; the smaller the unit, the more accurate the model.

Until now the best modeling programs could achieve 0.2 mm in each direction. Cardioid can get down to 0.1 mm. Where previously researchers could run the simulations for tens of heartbeats, Cardioid executing on Sequoia captures thousands of heartbeats.

Scientists are seeing 300-fold speedups. It used to take 45 minutes to simulate just one beat, but now researchers can simulate an hour of heart activity – several thousand heartbeats – in seven hours.

With the less sophisticated codes, it was impossible to model the heart’s response to a drug or perform an electrocardiogram trace for a particular heart disorder. That kind of testing requires longer run times, which just wasn’t possible before Cardioid.

The model could potentially test a range of drugs and devices like pacemakers to examine their affect on the heart, paving the way for safer and more effective human testing. But it is especially suited to studying arrhythmia, a disorder of the heart in which the organ does not pump blood efficiently. Arrhythmias can lead to congestive heart failure, an inability of the heart to supply sufficient blood flow to meet the needs of the body.

There are various types of medications that disrupt cardiac rhythms. Even those designed to prevent arrhythmias can be harmful to some patients, and researchers do not yet fully understand exactly what causes these negative side effects. Cardioid will enable LLNL scientists to examine heart function as an anti-arrhythmia drug enters the bloodstream. They’ll be able to identify when drug levels are highest and when they drop off.

“Observing the full range of effects produced by a particular drug takes many hours,” noted computational scientist Art Mirin of LLNL. “With Cardioid, heart simulations over this timeframe are now possible for the first time.”

The Livermore–IBM team is also working on a mechanical model that simulates the contraction of the heart and pumping of blood. The electrical and mechanical simulations will be allowed to interact with each other, adding more realism to the heart model.

It’s not entirely clear why a national defense lab took on this heart simulation work. Fred Streitz, director of the Institute for Scientific Computing Research at LLNL, would say only that “there are legitimate national security implications for understanding how drugs affect human organs,” adding that the project stretched the limits of supercomputing in a manner that is relatable to the American people.

The cardiac modeling work was performed during the system’s “shakedown period” – the set-up and testing phase – and the team had to hurry to finish in the allotted time span. Once Sequoia becomes classified, it’s unclear if it will still be available to run Cardioid and other unclassified programs, although access will certainly be more difficult since the machine’s principle mission is running nuclear weapons codes.

Sequoia is an integral part of the NNSA’s Advanced Simulation and Computing (ASC) program, which is run by partner organizations LLNL, Los Alamos National Laboratory and Sandia National Laboratories. With 96 racks, 98,304 compute nodes, 1.6 million cores, and 1.6 petabytes of memory, Sequoia will help the NNSA fulfill its mission to “maintain and enhance the safety, security, reliability and performance of the U.S. nuclear weapons stockpile without nuclear testing.”

The Cardioid simulation has been named as a finalist in the 2012 Gordon Bell Prize competition, awarded each year to recognize supercomputing’s crowning achievements. Research partners, Streitz, Richards, and Mirin, will reveal their results at the Supercomputing Conference in Salt Lake City, Utah, on November 13.

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!

2017 Gordon Bell Prize Finalists Named

October 23, 2017

The three finalists for this year’s Gordon Bell Prize in High Performance Computing have been announced. They include two papers on projects run on China’s Sunway TaihuLight system and a third paper on 3D image recon Read more…

By John Russell

Data Vortex Users Contemplate the Future of Supercomputing

October 19, 2017

Last month (Sept. 11-12), HPC networking company Data Vortex held its inaugural users group at Pacific Northwest National Laboratory (PNNL) bringing together about 30 participants from industry, government and academia t Read more…

By Tiffany Trader

AI Self-Training Goes Forward at Google DeepMind

October 19, 2017

DeepMind, Google’s AI research organization, announced today in a blog that AlphaGo Zero, the latest evolution of AlphaGo (the first computer program to defeat a Go world champion) trained itself within three days to play Go at a superhuman level (i.e., better than any human) – and to beat the old version of AlphaGo – without leveraging human expertise, data or training. Read more…

By Doug Black

HPE Extreme Performance Solutions

Transforming Genomic Analytics with HPC-Accelerated Insights

Advancements in the field of genomics are revolutionizing our understanding of human biology, rapidly accelerating the discovery and treatment of genetic diseases, and dramatically improving human health. Read more…

Researchers Scale COSMO Climate Code to 4888 GPUs on Piz Daint

October 17, 2017

Effective global climate simulation, sorely needed to anticipate and cope with global warming, has long been computationally challenging. Two of the major obstacles are the needed resolution and prolonged time to compute Read more…

By John Russell

Data Vortex Users Contemplate the Future of Supercomputing

October 19, 2017

Last month (Sept. 11-12), HPC networking company Data Vortex held its inaugural users group at Pacific Northwest National Laboratory (PNNL) bringing together ab Read more…

By Tiffany Trader

AI Self-Training Goes Forward at Google DeepMind

October 19, 2017

DeepMind, Google’s AI research organization, announced today in a blog that AlphaGo Zero, the latest evolution of AlphaGo (the first computer program to defeat a Go world champion) trained itself within three days to play Go at a superhuman level (i.e., better than any human) – and to beat the old version of AlphaGo – without leveraging human expertise, data or training. Read more…

By Doug Black

Student Cluster Competition Coverage New Home

October 16, 2017

Hello computer sports fans! This is the first of many (many!) articles covering the world-wide phenomenon of Student Cluster Competitions. Finally, the Student Read more…

By Dan Olds

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan Read more…

By John Russell

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Intel Debuts Programmable Acceleration Card

October 5, 2017

With a view toward supporting complex, data-intensive applications, such as AI inference, video streaming analytics, database acceleration and genomics, Intel i Read more…

By Doug Black

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

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

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Leading Solution Providers

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

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