Page-based software DSM systems suffer from false sharing caused by the large sharing granularity, and only support one-dimension Block or Cyclicblock data distribution schemes. Thus applications running on them will...Page-based software DSM systems suffer from false sharing caused by the large sharing granularity, and only support one-dimension Block or Cyclicblock data distribution schemes. Thus applications running on them will suffer from poor data locality and will be able to exploit parallelism only when using a large number of processors. In this paper, a way towards supporting flexible data distribution (FDD) on software DSM system is presented. Small granularity-tunable blocks, the size of which can be set by compiler or programmer, are used to overlap the working data sets distributed among processors. The FDD was implemented on a software DSM system called JIAJIA. Compared with Block/Cyclic-block distribution schemes used by most DSM systems now, experiments show that the proposed way of flexible data distribution is more effective. The performance of the applications used in the experiments is significantly improved.展开更多
基金The work of this paper is supported by the National '863' High-Tech Programme of China under grant No. 863-306-ZD01-02- 5 and N
文摘Page-based software DSM systems suffer from false sharing caused by the large sharing granularity, and only support one-dimension Block or Cyclicblock data distribution schemes. Thus applications running on them will suffer from poor data locality and will be able to exploit parallelism only when using a large number of processors. In this paper, a way towards supporting flexible data distribution (FDD) on software DSM system is presented. Small granularity-tunable blocks, the size of which can be set by compiler or programmer, are used to overlap the working data sets distributed among processors. The FDD was implemented on a software DSM system called JIAJIA. Compared with Block/Cyclic-block distribution schemes used by most DSM systems now, experiments show that the proposed way of flexible data distribution is more effective. The performance of the applications used in the experiments is significantly improved.
