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Fifth IEEE International Conference on Cluster Computing (CLUSTER'03)
Improving the Performance of MPI Derived Datatypes by Optimizing Memory-Access Cost
Hong Kong
December 01-December 04
ISBN: 0-7695-2066-9
Surendra Byna, Illinois Institute of Technology
William Gropp, Argonne National Laboratory
Xian-He Sun, Illinois Institute of Technology
Rajeev Thakur, Argonne National Laboratory
The MPI Standard supports derived datatypes, which allow users to describe noncontiguous memory layout and communicate noncontiguous data with a single communication function. This feature enables an MPI implementation to optimize the transfer of noncontiguous data. In practice, however, few MPI implementations implement derived datatypes in a way that performs better than what the user can achieve by manually packing data into a contiguous buffer and then calling an MPI function. In this paper, we present a technique for improving the performance of derived datatypes by automatically using packing algorithms that are optimized for memory-access cost. The packing algorithms use memory-optimization techniques that the user cannot apply easily without advanced knowledge of the memory architecture. We present performance results for a matrix-transpose example that demonstrate that our implementation of derived datatypes significantly outperforms both manual packing by the user and the existing derived-datatype code in the MPI implementation (MPICH).
Citation:
Surendra Byna, William Gropp, Xian-He Sun, Rajeev Thakur, "Improving the Performance of MPI Derived Datatypes by Optimizing Memory-Access Cost," cluster, pp.412, Fifth IEEE International Conference on Cluster Computing (CLUSTER'03), 2003
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