Physics Data Processing at NERSC Dramatically Cuts Reconstruction Time

February 14, 2018

Feb. 14, 2018 — In a recent demonstration project, physicists from Brookhaven National Laboratory (BNL) and Lawrence Berkeley National Laboratory (Berkeley Lab) used the Cori supercomputer at the National Energy Research Scientific Computing Center (NERSC) to reconstruct data collected from a nuclear physics experiment, an advance that could dramatically reduce the time it takes to make detailed data available for scientific discoveries.

The researchers reconstructed multiple datasets collected by the STAR (Solenoidal Tracker At RHIC) detector during particle collisions at the Relativistic Heavy Ion Collider (RHIC), a nuclear physics research facility at BNL. By running multiple computing jobs simultaneously on the allotted supercomputing cores, the team transformed raw data into “physics-ready” data at the petabyte scale in a fraction of the time it would have taken using in-house high-throughput computing resources—even with a two-way transcontinental journey via ESnet, the Department of Energy’s high-speed, high-performance data-sharing network that is managed by Berkeley Lab.

Preparing raw data for analysis typically takes many months, making it nearly impossible to provide such short-term responsiveness, according to Jérôme Lauret, a senior scientist at BNL and co-author on a paper outlining this work that was published in the Journal of Physics.

“This is a key usage model of high performance computing (HPC) for experimental data, demonstrating that researchers can get their raw data processing or simulation campaigns done in a few days or weeks at a critical time instead of spreading out over months on their own dedicated resources,” said Jeff Porter, a member of the data and analytics services team at NERSC and co-author on the Journal of Physics paper.

Billions of Data Points

The STAR experiment is a leader in the study of strongly interacting QCD matter that is generated in energetic heavy ion collisions. STAR consists of a large, complex set of detector systems that measure the thousands of particles produced in each collision event. Detailed analyses of billions of such collisions have enabled STAR scientists to make fundamental discoveries and measure the properties of the quark-gluon plasma. Since RHIC started running in the year 2000, this raw data processing, or reconstruction, has been carried out on dedicated computing resources at the RHIC and ATLAS Computing Facility (RACF) at BNL. High-throughput computing clusters crunch the data event by event and write out the coded details of each collision to a centralized mass storage space accessible to STAR physicists around the world.

In recent years, however, STAR datasets have reached billions of events, with data volumes at the multi-petabyte scale. The raw data signals collected by the detector electronics are processed using sophisticated pattern recognition algorithms to generate the higher-level datasets that are used for physics analysis. So the STAR computing team investigated the use of external resources to meet the demand for timely access to physics-ready data, ultimately turning to NERSC. Among other things, NERSC operates the PDSF cluster for the HEP/NP experiment community, which represents the second largest compute cluster available to the STAR collaboration.

A Processing Framework

Unlike the high-throughput computers at the RACF and PDSF, which analyze events one by one, HPC resources like those at NERSC break large problems into smaller tasks that can run in parallel. So the challenge was to parallelize the processing of STAR event data in a way that can scale out to run on large amounts of data with reproducible results.

The processing framework run at NERSC was built upon several core features. Shifter, a Linux container system developed at NERSC, provided a simple solution to the difficult problem of porting complex software to new computing systems and keep its expected behavior. Scalability was achieved by eliminating bottlenecks in accessing both the event data and experiment databases that record environmental changes—voltage, temperature, pressure and other detector conditions—during data taking. To do this, the workload was broken up into data chunks, sized to run on a single node onto which a snapshot of the STAR database could also be stored. Each node was then self-sufficient, allowing the work to automatically expand out to as many nodes as available without any direct intervention.

“Several technologies developed in-house at NERSC allowed us to build a highly fault-tolerant, multi-step, data-processing pipeline that could scale to practically unlimited number of nodes with the potential to dramatically fold the time it takes to process data for many experiments,” noted Mustafa Mustafa a Berkeley Lab physicist who helped design the system.

Another challenge in migrating the task of raw data reconstruction to an HPC environment was getting the data from BNL in New York to NERSC in California and back. Both the input and output datasets are huge. The team started small with a proof-of-principle experiment—just a few hundred jobs—to see how their new workflow programs would perform. Colleagues at RACF, NERSC and ESnet—including Damian Hazen of NERSC and Eli Dart of ESnet—helped identify hardware issues and optimize the data transfer and the end-to-end workflow.

After fine-tuning their methods based on the initial tests, the team started scaling up, initially using 6,400 computing cores on Cori; in their most recent test they utilized 25,600 cores. The end-to-end efficiency of the entire process—the time the program was running (not sitting idle, waiting for computing resources) multiplied by the efficiency of using the allotted supercomputing slots and getting useful output all the way back to BNL—was 98 percent.

“This was a very successful large-scale data processing run on NERSC HPC,“ said Jan Balewski, a member of the data science engagement group at NERSC who worked on this project. “One that we can look to as a reference as we actively test alternative approaches to support scaling up the computing campaigns at NERSC by multiple physics experiments.”

About NERSC and Berkeley Lab

The National Energy Research Scientific Computing Center (NERSC) is a U.S. Department of Energy Office of Science User Facility that serves as the primary high-performance computing center for scientific research sponsored by the Office of Science. Located at Lawrence Berkeley National Laboratory, the NERSC Center serves more than 6,000 scientists at national laboratories and universities researching a wide range of problems in combustion, climate modeling, fusion energy, materials science, physics, chemistry, computational biology, and other disciplines. Berkeley Lab is a DOE national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California for the U.S. DOE Office of Science. »Learn more about computing sciences at Berkeley Lab.


Source: NERSC

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!

Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Francisco, one would be tempted to dismiss its claims of inventing Read more…

By John Russell

Silicon Startup Raises ‘Prodigy’ for Hyperscale/AI Workloads

May 23, 2018

There's another silicon startup coming onto the HPC/hyperscale scene with some intriguing and bold claims. Silicon Valley-based Tachyum Inc., which has been emerging from stealth over the last year and a half, is unveili Read more…

By Tiffany Trader

Scientists Conduct First Quantum Simulation of Atomic Nucleus

May 23, 2018

OAK RIDGE, Tenn., May 23, 2018—Scientists at the Department of Energy’s Oak Ridge National Laboratory are the first to successfully simulate an atomic nucleus using a quantum computer. The results, published in Ph Read more…

By Rachel Harken, ORNL

HPE Extreme Performance Solutions

HPC and AI Convergence is Accelerating New Levels of Intelligence

Data analytics is the most valuable tool in the digital marketplace – so much so that organizations are employing high performance computing (HPC) capabilities to rapidly collect, share, and analyze endless streams of data. Read more…

IBM Accelerated Insights

Mastering the Big Data Challenge in Cognitive Healthcare

Patrick Chain, genomics researcher at Los Alamos National Laboratory, posed a question in a recent blog: What if a nurse could swipe a patient’s saliva and run a quick genetic test to determine if the patient’s sore throat was caused by a cold virus or a bacterial infection? Read more…

First Xeon-FPGA Integration Launched by Intel

May 22, 2018

Ever since Intel’s acquisition of FPGA specialist Altera in 2015 for $16.7 billion, it’s been widely acknowledged that some day, Intel would release a processor that integrates its mainstream Xeon CPU server chip wit Read more…

By Doug Black

Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Franci Read more…

By John Russell

Silicon Startup Raises ‘Prodigy’ for Hyperscale/AI Workloads

May 23, 2018

There's another silicon startup coming onto the HPC/hyperscale scene with some intriguing and bold claims. Silicon Valley-based Tachyum Inc., which has been eme Read more…

By Tiffany Trader

Japan Meteorological Agency Takes Delivery of Pair of Crays

May 21, 2018

Cray has supplied two identical Cray XC50 supercomputers to the Japan Meteorological Agency (JMA) in northwestern Tokyo. Boasting more than 18 petaflops combine Read more…

By Tiffany Trader

ASC18: Final Results Revealed & Wrapped Up

May 17, 2018

It was an exciting week at ASC18 in Nanyang, China. The student teams braved extreme heat, extremely difficult applications, and extreme competition in order to cross the cluster competition finish line. The gala awards ceremony took place on Wednesday. The auditorium was packed with student teams, various dignitaries, the media, and other interested parties. So what happened? Read more…

By Dan Olds

Spring Meetings Underscore Quantum Computing’s Rise

May 17, 2018

The month of April 2018 saw four very important and interesting meetings to discuss the state of quantum computing technologies, their potential impacts, and th Read more…

By Alex R. Larzelere

Quantum Network Hub Opens in Japan

May 17, 2018

Following on the launch of its Q Commercial quantum network last December with 12 industrial and academic partners, the official Japanese hub at Keio University is now open to facilitate the exploration of quantum applications important to science and business. The news comes a week after IBM announced that North Carolina State University was the first U.S. university to join its Q Network. Read more…

By Tiffany Trader

Democratizing HPC: OSC Releases Version 1.3 of OnDemand

May 16, 2018

Making HPC resources readily available and easier to use for scientists who may have less HPC expertise is an ongoing challenge. Open OnDemand is a project by t Read more…

By John Russell

PRACE 2017 Annual Report: Exascale Aspirations; Industry Collaboration; HPC Training

May 15, 2018

The Partnership for Advanced Computing in Europe (PRACE) today released its annual report showcasing 2017 activities and providing a glimpse into thinking about Read more…

By John Russell

MLPerf – Will New Machine Learning Benchmark Help Propel AI Forward?

May 2, 2018

Let the AI benchmarking wars begin. Today, a diverse group from academia and industry – Google, Baidu, Intel, AMD, Harvard, and Stanford among them – releas Read more…

By John Russell

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

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

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

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

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

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17

Altair

AMD @ SC17

AMD

ASRock Rack @ SC17

ASRock Rack

CEJN @ SC17

CEJN

DDN Storage @ SC17

DDN Storage

Huawei @ SC17

Huawei

IBM @ SC17

IBM

IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17

Intel

Lenovo @ SC17

Lenovo

Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17

Microsoft

Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17

Supericro

Tyan @ SC17

Tyan

Univa @ SC17

Univa

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

CFO Steps down in Executive Shuffle at Supermicro

January 31, 2018

Supermicro yesterday announced senior management shuffling including prominent departures, the completion of an audit linked to its delayed Nasdaq filings, and Read more…

By John Russell

HPE Wins $57 Million DoD Supercomputing Contract

February 20, 2018

Hewlett Packard Enterprise (HPE) today revealed details of its massive $57 million HPC contract with the U.S. Department of Defense (DoD). The deal calls for HP Read more…

By Tiffany Trader

Deep Learning Portends ‘Sea Change’ for Oil and Gas Sector

February 1, 2018

The billowing compute and data demands that spurred the oil and gas industry to be the largest commercial users of high-performance computing are now propelling Read more…

By Tiffany Trader

Nvidia Ups Hardware Game with 16-GPU DGX-2 Server and 18-Port NVSwitch

March 27, 2018

Nvidia unveiled a raft of new products from its annual technology conference in San Jose today, and despite not offering up a new chip architecture, there were still a few surprises in store for HPC hardware aficionados. Read more…

By Tiffany Trader

Hennessy & Patterson: A New Golden Age for Computer Architecture

April 17, 2018

On Monday June 4, 2018, 2017 A.M. Turing Award Winners John L. Hennessy and David A. Patterson will deliver the Turing Lecture at the 45th International Sympo Read more…

By Staff

Part One: Deep Dive into 2018 Trends in Life Sciences HPC

March 1, 2018

Life sciences is an interesting lens through which to see HPC. It is perhaps not an obvious choice, given life sciences’ relative newness as a heavy user of H Read more…

By John Russell

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