消息传递与工作站网络上的分布式共享内存

Honghui Lu, S. Dwarkadas, A. Cox, W. Zwaenepoel
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引用次数: 112

摘要

消息传递程序使用PVM (Parallel Virtual Machine)库执行,共享内存程序使用TreadMarks执行。这些程序是SPLASH基准套件中的Water和Barnes-Hut;NAS基准中的3-D FFT、整数排序(IS)和尴尬并行(EP)ILINK,一个广泛使用的遗传连锁分析程序;连续超松弛法(SOR)、旅行推销员法(TSP)和快速排序法(QSORT)。两种不同的输入数据集用于Water (Water-288和Water-1728)、IS (IS- small和IS- large)和SOR (SOR- zero和SOR- nonzero)。我们的执行环境是一组8个HP735工作站,通过每秒100mbit / s的FDDI网络连接。对于Water-1728、EP、ILINK、SOR-Zero和SOR-NonZero, TreadMarks的性能在PVM的10%以内。对于IS-Small、Water-288、Barnes-Hut、3-D FFT、TSP和QSORT,差异在10%到30%之间。最后,对于IS-Large, PVM的性能是TreadMarks的两倍。在TreadMarks中发送了更多的消息和数据,这解释了性能差异。这种额外的通信是由以下原因造成的:1)同步和数据传输的分离,2)在TreadMarks中使用的invalidate协议请求更新数据的额外消息,3)错误共享,4)在TreadMarks中迁移数据的困难积累。
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Message Passing Versus Distributed Shared Memory on Networks of Workstations
The message passing programs are executed with the Parallel Virtual Machine (PVM) library and the shared memory programs are executed using TreadMarks. The programs are Water and Barnes-Hut from the SPLASH benchmark suite; 3-D FFT, Integer Sort (IS) and Embarrassingly Parallel (EP) from the NAS benchmarks; ILINK, a widely used genetic linkage analysis program; and Successive Over-Relaxation (SOR), Traveling Salesman (TSP), and Quicksort (QSORT). Two different input data sets were used for Water (Water-288 and Water-1728), IS (IS-Small and IS-Large), and SOR (SOR-Zero and SOR-NonZero). Our execution environment is a set of eight HP735 workstations connected by a 100Mbits per second FDDI network. For Water-1728, EP, ILINK, SOR-Zero, and SOR-NonZero, the performance of TreadMarks is within 10%of PVM. For IS-Small, Water-288, Barnes-Hut, 3-D FFT, TSP, and QSORT, differences are on the order of 10%to 30%. Finally, for IS-Large, PVM performs two times better than TreadMarks. More messages and more data are sent in TreadMarks, explaining the performance differences. This extra communication is caused by 1) the separation of synchronization and data transfer, 2) extra messages to request updates for data by the invalidate protocol used in TreadMarks, 3) false sharing, and 4) diff accumulation for migratory data in TreadMarks.
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