Research on hierarchical macro-data-flow parallel processing on SMP-cluster

SMP集群层次化宏数据流并行处理研究

基本信息

批准号：
16500025
负责人：
HONDA Hiroki
金额：
$ 2.43万
依托单位：
The University of Electro-Communications
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2006
项目状态：
已结题

项目摘要

The objective of this research is developing the scheme to realize the hierarchical macro-data-flow parallel processing, which exploits the parallelism among coarse-grain tasks, on the SMP (symmetrical multi processor)-cluster which has hierarchical H/W parallelisms.In order to realize macro-dataflow parallel processing on SMP-cluster, "data reaching conditions", a method to make the sender-receiver pair of a data transfer determined at run time, has previously been proposed by the investigator of this research. The originality of this research lies in both implementing macro-dataflow with the method on real systems and extending the method to HIERARCHICAL macro-data flow parallel processing.The implementation and evaluation of the hierarchical macro-dataflow processing on SMP-cluster have been done on the SMP-cluster parched by this grant. The results of this research show that the method for hierarchical macro-dataflow parallel processing on SMP-cluster achieves the high efficient parallel processing.In addition, we have expanded the method to realize the macro-dataflow parallel processing on software distributed shared memory and showed the effectiveness of the method.The results of this research have been published on the IPSJ transaction, IEEE International Conference on Cluster Computing, Symposium on Advanced Computing Systems and Infrastructures(SACSIS) and some IPSJ SIG Technical Reports.

The objective of this research is developing the scheme to realize the hierarchical macro-data-flow parallel processing, which exploits the parallelism among coarse-grain tasks, on the SMP (symmetrical multi processor)-cluster which has hierarchical H/W parallelisms.In order to realize macro-dataflow parallel processing on SMP-cluster, "data reaching conditions", a method to make the sender-receiver pair of a data transfer在运行时确定，该研究的研究者先前提出了此前提出的。这项研究的独创性在于用实际系统上的方法实施宏数据流，并将方法扩展到层次宏数据流并行处理。对SMP群集的层次宏数据流处理的实施和评估已在SMP群集上完成。这项研究的结果表明，在SMP群集上平行层次宏观数据平行处理的方法可实现高效并行处理。此外，我们扩展了该方法，以实现对软件分布式共享内存的宏观数据平行处理，并显示了该方法的有效性。基础架构（SACSIS）和一些IPSJ SIG技术报告。