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Parallel out-of-core Matlab for extreme virtual memory (Abstract)

Published in:
2005 IEEE Int. Conf. on Cluster Computing, 27-30 September 2005, p. 482 [abstract only].

Summary

Large data sets that cannot fit in memory can be addressed with out-of-core methods, which use memory as a "window" to view a section of the data stored on disk at a time. The Parallel Matlab for eXtreme Virtual Memory (pMatlab XVM) library adds out-of-core extensions to the Parallel Matlab (pMatlab) library. We have applied pMatlab XVM to the DARPA High Productivity Computing Systems? HPCchallenge FFT benchmark. The benchmark was run using several different implementations: C+MPI, pMatlab, pMatlab hand coded for out-of-core and pMatlab XVM. These experiments found 1) the performance of the C+MPI and pMatlab versions were comparable; 2) the out-of-core versions deliver 80% of the performance of the in-core versions; 3) the out-of-core versions were able to perform a 1 terabyte (64 billion point) FFT and 4) the pMatlab XVM program was smaller, easier to implement and verify, and more efficient than its hand coded equivalent. We are transitioning this technology to several DoD signal processing applications and plan to apply pMatlab XVM to the full HPCchallenge benchmark suite. Using next generation hardware, problems sizes a factor of 100 to 1000 times larger should be feasible.
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Summary

Large data sets that cannot fit in memory can be addressed with out-of-core methods, which use memory as a "window" to view a section of the data stored on disk at a time. The Parallel Matlab for eXtreme Virtual Memory (pMatlab XVM) library adds out-of-core extensions to the Parallel Matlab...

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Parallel MATLAB for extreme virtual memory

Published in:
Proc. of the HPCMP Users Group Conf., 27-30 June 2005, pp. 381-387.

Summary

Many DoD applications have extreme memory requirements, often with data sets larger than memory on a single computer. Such data sets can be addressed with out-of-core methods, which use memory as a "window" to view a section of the data stored on disk at a time. The Parallel Matlab for eXtreme Virtual Memory (pMatlab XVM) library adds out-of-core extensions to the Parallel Matlab (pMatlab) library. The DARPA High Productivity Computing Systems' HPC challenge FFT benchmark has been implemented in C+MPI, pMatlab, pMatlab hand coded for out-of-core and pMatlab XVM. We found that 1) the performance of the C+MPI and pMatlab versions were comparable; 2) the out-of-core versions deliver 80% of the performance of the in-core versions; 3) the out-of-core versions were able to perform a 1 TB (64 billion point) FFT; and 4) the pMatlab XVM program was smaller, easier to implement and verify, and more efficient than its hand coded equivalent. We plan to apply pMatlab XVM to the full HPC challenge benchmark suite. Using next generation hardware, problems sizes a factor of 100 to 1000 times larger should be feasible. We are also transitioning this technology to several DoD signal processing applications. Finally, the flexibility of pMatlab XVM allows hardware designers to experiment with FFT parameters in software before designing hardware for a real-time, ultra-long FFT.
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Summary

Many DoD applications have extreme memory requirements, often with data sets larger than memory on a single computer. Such data sets can be addressed with out-of-core methods, which use memory as a "window" to view a section of the data stored on disk at a time. The Parallel Matlab for...

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