Graph500 adds new measurement of supercomputing performance

Jun 26, 2012

(Phys.org) -- Supercomputing performance is getting a new measurement with the Graph500 executive committee’s announcement of specifications for a more representative way to rate the large-scale data analytics at the heart of high-performance computing.

An international team that includes Sandia National Laboratories announced the single-source shortest-path specification to assess computing performance on Tuesday at the International Supercomputing Conference in Hamburg, Germany.

The latest benchmark “highlights the importance of new systems that can find the proverbial needle in the haystack of data,” said Graph500 executive committee member David A. Bader, a professor in the School of Computational Science and Engineering and executive director of High-Performance Computing at the Georgia Institute of Technology.

The new specification will measure the closest distance between two things, said Sandia National Laboratories researcher Richard Murphy, who heads the executive committee. For example, it would seek the smallest number of people between two people chosen randomly in the professional network LinkedIn, finding the fewest friend of a friend of a friend links between them, he said.

Graph500 already gauges two computational techniques, called kernels: a large graph that links huge numbers of participants and a parallel search of that graph. The first two kernels were relatively easy problems; this third one is harder, Murphy said. Once it’s been tested, the next kernel will be harder still, he said.

The rankings are oriented toward enormous graph-based data problems, a core part of most analytics workloads. Graph500 rates machines on their ability to solve complex problems that have seemingly infinite numbers of components, rather than ranking machines on how fast they solve those problems.

Big data problems represent a $270 billion market and are increasingly important for businesses such as Google, Facebook and LexisNexis, Murphy said.

Large data problems are especially important in cybersecurity, medical informatics, data enrichment, social networks and symbolic networks. Last year, the Obama administration announced a push to develop better big data systems.

Problems that require enormously complex graphs include correlating medical records of millions of patients, analyzing ever-growing numbers of electronically related participants in social media and dealing with symbolic networks, such as tracking tens of thousands of shipping containers of goods roaming the world’s oceans.

Medical-related data alone could potentially overwhelm all of today’s high-performance computing, Murphy said.

Graph500’s steering committee is made up of more than 30 international experts in high-performance computing who work on what benchmarks supercomputers should meet in the future. The executive committee, which implements changes in the benchmark, includes Sandia, Argonne National Laboratory, Georgia Institute of Technology and Indiana University.

Bader said emerging applications in healthcare informatics, social network analysis, web science and detecting anomalies in financial transactions “require a new breed of data-intensive supercomputers that can make sense of massive amounts of information.”

But performance can’t be improved without a meaningful benchmark, Murphy said.

“The whole goal is to spur industry to do something harder” as they jockey for top rankings, he said.

“If there’s a change in the list over time — and there should be — it’s a big deal,” he added.

Murphy sees Graph500 as a complementary performance yardstick to the well-known Top 500 rankings of supercomputer performance, based on speed processing the Linpack code. Nine computers made the first Graph500 list in November 2010; by last November, the number had grown to 50. Its fourth list, released at the conference in Germany, ranked 88. Rankings are released twice a year at the Supercomputing Conference in November and the International Supercomputing Conference in June.

“A machine on the top of this list may analyze huge quantities of data to provide better and more personalized health care decisions, improve weather and climate prediction, improve our cybersecurity and better integrate our online social networks with our personal lives,” Bader said.

Explore further: Coping with floods—of water and data

More information: www.graph500.org/

add to favorites email to friend print save as pdf

Related Stories

New standard proposed for supercomputing

Nov 15, 2010

A new supercomputer rating system will be released by an international team led by Sandia National Laboratories at the Supercomputing Conference 2010 in New Orleans on Nov. 17.

PRIMEHPC FX10 supercomputer wins crown for Fujitsu

Nov 08, 2011

(PhysOrg.com) -- Fujitsu yesterday announced a new commercial supercomputer, the PRIMEHPC FX10. The announcement is a stunner because of its specs, and right on the heels of this month’s other Fujitsu ...

Student pursues breakthrough in supercomputing

Jun 29, 2011

A Northeastern University undergraduate is leading the development of a new process that will make it possible for certain supercomputers to save their data midway through a computation, preventing the loss ...

Recommended for you

Coping with floods—of water and data

Dec 19, 2014

Halloween 2013 brought real terror to an Austin, Texas, neighborhood, when a flash flood killed four residents and damaged roughly 1,200 homes. Following torrential rains, Onion Creek swept over its banks and inundated the ...

Cloud computing helps make sense of cloud forests

Dec 17, 2014

The forests that surround Campos do Jordao are among the foggiest places on Earth. With a canopy shrouded in mist much of time, these are the renowned cloud forests of the Brazilian state of São Paulo. It is here that researchers ...

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.