Blacklight Goes to Work at the Pittsburgh Supercomputing Center
The world’s largest shared-memory system, a resource of XSEDE, has rapidly proven itself as a productive tool in research across a range of fields.
PITTSBURGH,November 9, 2011 — Blacklight has rapidly proven its mettle in many scientific fields. This newest system of the Pittsburgh Supercomputing Center (PSC), an SGI® Altix® UV1000, acquired in July 2010 with help from a $2.8 million award from the National Science Foundation, is a resource of XSEDE, the NSF cyberinfrastructure program, where it has opened new capability for U.S. scientists and engineers. With 512 eight-core Intel Xeon 7500 (Nehalem) processors (4,096 cores) and 32 terabytes of memory, Blacklight is partitioned into two connected 16-terabyte coherent shared-memory systems — the two largest shared-memory systems in the world.
In work since October 2010, when Blacklight became available for NSF allocations, it has enabled advances in fields that include nanomaterials, genomics, machine learning, astrophysics, geophysics, natural language processing and climate modeling.
“As we expected it would, Blacklight has opened new doors to high-performance computation in many research communities,” said PSC scientific directors Michael Levine and Ralph Roskies, “and rapidly become a force across a wide and interesting spectrum of fields.”
“Blacklight represents the leading edge in technical computing,” said SGI CEO Mark J. Barrenechea. “With this platform, the scientific community will find answers to some of the toughest questions and make new discoveries with significant impact throughout the world for years to come. We are delighted to work with the Pittsburgh Supercomputing Center to advance these efforts.”
For astrophysicists Tiziana Di Matteo and Rupert Croft, Blacklight has revolutionized discovery from large-scale simulations of how the cosmos evolves. The ability to hold an entire snapshot of their MassiveBlack simulation (between three and four terabytes of data) in memory at one time was instrumental in their ability to reveal “cold gas flows” as a phenomenon that accounts for supermassive black holes in the early universe, resolving what had been a puzzle in the Cold Dark Matter model of the universe. See http://www.psc.edu/science/2011/supermassive
“Flux ropes” from simulations by Homa Karimabadi and collaborators. “Blacklight’s shared-memory architecture,” says Karimabadi, “is critical for analysis of these massive datasets.”
In a large geophysics project, a team of physicists used Blacklight to produce scientific visualizations that made it possible to see a fundamental phenomenon of space weather called magnetic reconnection, which can disrupt satellites, spacecraft and power grids on Earth. The researchers used XSEDE resources (Kraken at the National Institute for Computational Sciences, University of Tennessee, Knoxville) for very large simulations that characterize how turbulence within sheets of electrons generates structures — called “flux ropes” — that play a large role in magnetic reconnection. “One run can generate more than 200 terabytes,” says physicist Homa Karimabadi of the University of California, San Diego. “Blacklight’s shared-memory architecture is critical for analysis of these massive datasets.” See http://www.psc.edu/science/2011/inprogress/#solarwind
In genomics, Blacklight has helped to open a potential bottleneck in processing of next-generation sequencing data. In one project, for instance, involving billions of 100-base reads from a sequencer, Blacklight’s shared-memory architecture — along with consulting help from XSEDE’s Extended Collaborative Support Services staff — made it possible to complete a de novo assembly in weeks, progress that had eluded James Vincent of the University of Vermont and colleagues in the Northeast Cyberinfrastructure Consortium for nearly a year in work with other systems. See http://www.psc.edu/science/2011/sequencing
With limitless quantities of text available on World Wide Web, Blacklight’s shared memory provides a powerful tool for natural language processing (NLP) — sifting through billions and billions of words in various applications, including automated translators, and innovative predictive modeling. Noah Smith of Carnegie Mellon University produced four studies in diverse areas of NLP within six months of access to Blacklight. “Blacklight has been a very useful resource for us,” says Smith. “We can incorporate deeper ideas about how language works, and we can estimate these more complex models on more data.” See http://www.psc.edu/science/2011/language
For more information about these projects and others on Blacklight, see PSC’s Projects in Scientific Computing: http://www.psc.edu/science/2011 (Available in hardcopy at PSC’s booth, #1123, at Supercomputing ’11, Seattle, Nov. 22-25.)
Blacklight Memory Advantage Program
To help researchers take advantage of Blacklight, PSC provides a Memory Advantage Program to develop applications that can effectively use Blacklight’s shared-memory capabilities. These include rapid expression of algorithms — such as graph-theoretical software, for which distributed memory often presents obstacles, and interactive analysis of large data sets, which often can be loaded in their entirety into Blacklight’s shared memory. For such projects, a PSC consultant can provide advice on debugging, performance-analysis and optimizations. Interested researchers may contact: email@example.com
In computer terms, “shared memory” means a system’s memory can be directly accessed from all of its processors, as opposed to distributed memory (in which each processor’s memory is directly accessed only by that processor). Because all processors share a single view of data, a shared memory system is, relatively speaking, easy to program and use.
The Pittsburgh Supercomputing Center is a joint effort of Carnegie Mellon University and the University of Pittsburgh together with Westinghouse Electric Company. Established in 1986, PSC is supported by several federal agencies, the Commonwealth of Pennsylvania and private industry, and is a partner in the National Science Foundation XSEDE program.