Visit additional Tabor Communication Publications
November 09, 2011
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, Nov. 9 -- 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."
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.
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. More about PSC at http://www.psc.edu.
Source: Pittsburgh Supercomputing Center
In quieter times, sounding the bell of funding big science with big systems tends to resonate further than when ears are already burning with sour economic and national security news. For exascale's future, however, the time could be ripe to instill some sense of urgency....
In a recent solicitation, the NSF laid out needs for furthering its scientific and engineering infrastructure with new tools to go beyond top performance, Having already delivered systems like Stampede and Blue Waters, they're turning an eye to solving data-intensive challenges. We spoke with the agency's Irene Qualters and Barry Schneider about..
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
May 22, 2013 |
At some point in the not-too-distant future, building powerful, miniature computing systems will be considered a hobby for high schoolers, just as robotics or even Lego-building are today. That could be made possible through recent advancements made with the Raspberry Pi computers.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
May 15, 2013 |
Supercomputers at the Department of Energy’s National Energy Research Scientific Computing Center (NERSC) have worked on important computational problems such as collapse of the atomic state, the optimization of chemical catalysts, and now modeling popping bubbles.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
In this demonstration of SGI DMF ZeroWatt disk solution, Dr. Eng Lim Goh, SGI CTO, discusses a function of SGI DMF software to reduce costs and power consumption in an exascale (Big Data) storage datacenter.
The Cray CS300-AC cluster supercomputer offers energy efficient, air-cooled design based on modular, industry-standard platforms featuring the latest processor and network technologies and a wide range of datacenter cooling requirements.