Abstract
A new class of algorithms is presented for efficiently carrying out many-to-many parallel data redistribution in a memory-limited environment. Key properties of these algorithms are explored, and their performance is compared using idealized benchmark problems. These algorithms form part of a newly developed MPI-based library MADRE (Memory-Aware Data Redistribution Engine), an open source toolkit designed for easy integration with application codes to improve their performance, portability, and scalability.
This research was supported by the National Science Foundation under Grants CCF-0733035 and CCF-0540948 and used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357.
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Siegel, S.F., Siegel, A.R. (2008). MADRE: The Memory-Aware Data Redistribution Engine. In: Lastovetsky, A., Kechadi, T., Dongarra, J. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 2008. Lecture Notes in Computer Science, vol 5205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87475-1_31
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DOI: https://doi.org/10.1007/978-3-540-87475-1_31
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