http://www.ll.mit.edu) has enabled its next generation LLGrid interactive/on-demand parallel computing system. This system was provided to Lincoln Laboratory via a DoD High Performance Computing Modernization Program...">
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June 15, 2007
MIT Lincoln Laboratory (http://www.ll.mit.edu) has enabled its next generation LLGrid interactive/on-demand parallel computing system. This system was provided to Lincoln Laboratory via a DoD High Performance Computing Modernization Program (HPCMP) Distributed High Performance Investment in collaboration with Dell Computer, Inc. The LLGrid system consists of ~1500 InfiniBand connected processors, ~6 Terabytes of RAM and ~0.8 Petabytes of local disk/virtual memory.
Lincoln Laboratory will use this system to develop, prototype, and transition next-generation signal and image processing algorithms for DoD applications. A critical element of the algorithm development process is interactive test and refinement, which require interactive/on-demand access using high-level programming environments.
LLGrid supports 200+ users at Lincoln Laboratory, ~85 percent of whom run parallel MATLAB codes using the Lincoln Laboratory developed pMatlab library (http://www.ll.mit.edu/pMatlab) or The Mathworks developed Distributed Computing Toolbox (DCT).
An important LLGrid subsystem is the TX-2500, which consists of over 400 servers each with a full 6-drive RAID storage system. This provides ~0.8 Petabytes of local high bandwidth storage for sensor data. It also provides a unique experimental platform for testing next-generation parallel file system technology. Using the Lincoln Laboratory pMatlab XVM (eXtreme Virtual Memory) software, the entire storage can be treated as a single large global array of data enabling data sets as large as 50,000 x 50,000 x 50,000 grid elements to be processed. [Note: The TX-2500 is named in honor of the TX-0 (http://en.wikipedia.org/wiki/TX-0) developed at Lincoln in the 1950s, the world's first interactive high performance computing system.]
The DoD HPCMP-mandated acceptance test was conducted using the HPC Challenge benchmark suite (http://www.HPCchallenge.org). This benchmark suite is designed to stress a wide variety of parallel components: processor, memory, network bandwidth, and network latency. As part of the acceptance test, Lincoln Laboratory ran 170 variations using different processors and memory sizes. This baseline performance data is now publicly available at the HPC Challenge website.
This work was sponsored by the Department of Defense under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions and recommendations are those of the authors and are not necessarily endorsed by the United States Government.
MATLAB and Distributed Computing Toolbox are registered trademarks of The MathWorks. Reference to commercial products, trade names, trademarks or manufacturer dots not constitute or imply endorsement.
MIT Lincoln Laboratory is a federally funded research and development center operated by the Massachusetts Institute of Technology under a contract with the U.S. Air Force. Serving multiple sponsors, the Laboratory conducts advanced R&D for national defense, with particular emphasis on advanced electronics and transfers technology to both government and industry.
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Source: MIT Lincoln Laboratory
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