Livermore Labs, IBM offer supercomputing access to industry

Researchers at Lawrence Livermore National Laboratory and IBM are joining forces to help boost industry’s competitiveness by giving partners access to supercomputing power.

IBM and LLNL have formed a collaboration called Deep Computing Solutions, to be housed within LLNL’s High Performance Computing Innovation Center, to help U.S. industry harness the power of supercomputing to better compete in the global marketplace.

Deep Computing Solutions will bring a new dimension to the HPCIC, adding IBM’s computational science expertise to LLNL’s own, for the benefit of Deep Computing Solution’s clients, IBM and LLNL officials said.


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“The capabilities of California’s Lawrence Livermore National Laboratory are uniquely suited to boost American industry’s competitiveness in the global marketplace,” said Sen. Dianne Feinstein, (D-Calif.). “The new collaboration between the lab and IBM is an excellent example of using the technical expertise of both the government and the private sector to spur innovation and investment in the U.S. economy."

She noted that LNNL’s supercomputing facilities offer a broad range of solutions to energy, environmental and national security problems.

Feinstein was set to deliver remarks on the collaboration on June 27 at a Capitol Hill briefing on "Big Data: The New Natural Resource." The focus of the briefing is to explore how Congress and the Obama administration can harvest big data to address the nation's pressing societal challenges.

LLNL intends for HPCIC to become the nation's premier provider of advanced computing solutions for third-party users. The Energy Department hosts quite a few of the world’s most powerful supercomputers, but their use is mostly restricted to government functions and academic research.

Computer and domain science experts from IBM Research and LLNL will work together with a broad range of U.S .industry collaborators to devise HPC solutions that can help accelerate the development of new technologies, products and services. Areas of interest include, but are not limited to, applied energy, green energy, biology, materials science, fabrication, manufacturing, data management and informatics.

“Maintaining a technological edge over the competition in the global marketplace is vital to both national security and the country’s economic prosperity,” said Frederick Streitz, director of the HPCIC. “Deep Computing Solutions will be an important ingredient of the HPC Innovation Center.”

“Deep Computing Solutions will deploy a comprehensive range of experienced researchers and developers from both IBM and LLNL to help develop robust solutions for its clients that can address enterprise-critical challenges, such as processing very large data sets to fuel competitive insights,” said James Sexton, program director, Computational Science Center, IBM T.J. Watson Research Center, N.Y.

High performance computing has the potential to provide groundbreaking impact in research and industrial applications. However, it has remained inaccessible to the broad community because its deployment requires access to special expertise and systems. LLNL's HPCIC and Deep Computing Solutions will directly address the accessibility problem that currently limits development and deployment of advanced computing solutions by commercial organizations, IBM and LLNL officials said.

LLNL has procured a 5 petaflop (5 quadrillion floating point operations per second) system to support HPCIC and Deep Computing Solutions efforts as well as unclassified National Nuclear Security Administration (NNSA) research programs, academic alliances and LLNL institutional science and technology efforts.

Called Vulcan, the new 24-rack IBM Blue Gene/Q system based on the Power architecture will be delivered in summer 2012. Vulcan is part of the contract that brought Sequoia, the 20-petaflop Blue Gene/Q machine recently ranked no. 1 on the TOP500 list of the world’s fastest supercomputers, to Livermore.

About the Author

Rutrell Yasin is is a freelance technology writer for GCN.

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