Enhancing Software DSM for Compiler-Parallelized Applications
In The 11th International Parallel Processing Symposium (IPPS), March 1996.
Pete Keleher and Chau-Wen Tseng
Abstract:
Current parallelizing compilers for message-passing machines only support a limited class of data-parallel applications. One method for eliminating this restriction is to combine powerful shared-memory parallelizing compilers with software distributed-shared-memory (DSM) systems. Preliminary results show simply combining the parallelizer and software DSM yields very poor performance. The compiler/software DSM interface can be improved based on relatively little compiler input by: 1) combining synchronization and parallelism information communication on parallel task invocation, 2) employing customized routines for evaluating reduction operations, and 3) selecting a hybrid update protocol to presend data by flushing updates at barriers. These optimizations yield decent speedups for program kernels, but are not sufficient for entire programs. Based on our experimental results, we point out areas where additional compiler analysis and software DSM improvements are necessary to achieve good performance.
@inProceedings{keleher-ipps96,
title = "Enhancing Software {DSM} for Compiler-Parallelized Applications",
author = "Pete Keleher and Chau-Wen Tseng",
booktitle = {The 11th International Parallel Processing Symposium (IPPS)},
month = {March},
year = {1996},
}
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