Transparent Adaptation of Sharing Granularity in MultiView-Based DSM Systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
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Data prefetching is a technique that a processing unit issues one or more non-blocking load operations before the very data items are actually required. The access latency of prefetching can be alleviated by overlapping it with other executions which are independent of the prefetched data. In distributed shared memory (DSM) systems, remote memory accesses take much longer than local ones and hence data prefetching should be effective for such systems. However, to our knowledge relatively few researches have been done for data prefetching on DSM systems. This paper is concerned with issues of supporting data prefetching on DSM systems. Our approach is to develop a new memory consistency semantic (MCS) model under which the prefetchable shared data objects, as well as the best moment to launch a prefetching operation, can be easily identified. Our new MCS, called the aggressive consistency, utilizes the coherence-on-demand concept and supports a special synchronization operation called SYNC, which also acts as the prefetching indicator. Preliminary simulation results show that our prefetching approach combined with the aggressive consistency can substantially improve the performance of DSM systems.