SDSC’s Flash ‘Gordon’ Too Fast for Retirement

By Tiffany Trader

March 15, 2017

They say a dog year is equivalent to about seven human years, but the average supercomputer’s lifespan is even shorter due mainly to the economics of powering and cooling the machines. A typical life cycle for today’s big iron is about five years, but sometimes another opportunity presents itself. Such is the case for “Gordon,” the San Diego Supercomputer Center (SDSC) system that was pioneering for its use of flash technology when it entered production in January 2012.

Five years goes by quickly, and now Gordon is nearing its official retirement date; on March 31, the data-focused machine ends its term as a National Science Foundation (NSF) resource. But that flash-enabled bandwidth, so valuable for today’s data heavy workloads, is proving to have staying power.

Yesterday, San Diego Supercomputer Center (SDSC) announced that “Gordon” will live on, thanks to an agreement with the Simons Foundation’s Flatiron Institute in New York. Flatiron will use Gordon’s computational power for ongoing research in astrophysics, biology, materials research and other fields according to an announcement put out by SDSC.

SDSC will provide high-performance computing (HPC) resources and services on Gordon for the Flatiron Institute as part of a two-year agreement, with an option to renew for a third year. The agreement takes effect April 1, 2017.

The contract guarantees Flatiron annual access to at least 90 percent of the machine’s cycles; SDSC will be able to use the remaining capacity within UC San Diego’s Center for Astrophysics & Space Sciences (CASS), SDSC’s OpenTopography project and various projects within the Center for Applied Internet Data Analysis (CAIDA), which is based at SDSC.

“We are delighted that the Simons Foundation has given Gordon a new lease on life after five years of service as a highly sought after XSEDE resource,” said SDSC Director Michael Norman, who also served as the principal investigator for Gordon. “We welcome the Foundation as a new partner and consider this to be a solid testimony regarding Gordon’s data-intensive capabilities and its myriad contributions to advancing scientific discovery.”

“We are excited to have a big boost to the processing capacity for our researchers and to work with the strong team from San Diego,” said Ian Fisk, co-director of the Scientific Computing Core (SCC), which is part of the Flatiron Institute.

David Spergel, director of the Flatiron Institute’s Center for Computational Astrophysics (CCA) said, “CCA researchers will use Gordon both for simulating the evolution and growth of galaxies, as well as for the analysis of large astronomical data sets.  Gordon offers us a powerful platform for attacking these challenging computational problems.”

Other projects that will continue to benefit from Gordon include the Simons Array (the successor to the POLARBEAR project) and Simons Observatory.

“POLARBEAR and The Simons Array, which will deploy the most powerful CMB (Cosmic Microwave Background) radiation telescope and detector system ever made, are two NSF supported astronomical telescopes that observe CMB, in essence the leftover ‘heat’ from the Big Bang in the form of microwave radiation,” said Brian Keating, a professor of physics at UC San Diego’s Center for Astrophysics & Space Sciences and a co-PI for the POLARBEAR/Simons Array project.

Through its NSF tenure, Gordon has supported research and education by more than 2,000 command-line users and over 7,000 gateway users, primarily through XSEDE-based resource allocations.

“One of Gordon’s most data-intensive tasks was to rapidly process raw data from almost one billion particle collisions as part of a project to help define the future research agenda for the Large Hadron Collider (LHC),” notes SDSC. “Gordon provided auxiliary computing capacity by processing massive data sets generated by one of the LHC’s two large general-purpose particle detectors used to find the elusive Higgs particle. The around-the-clock data processing run on Gordon was completed in about four weeks’ time, making the data available for analysis several months ahead of schedule.”

This story relied on reporting from SDSC. For more details, refer to the SDSC press release.

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