Towards implementation of a novel scheme for data prefetching on distributed shared memory systems |
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Authors: | Hsiao-Hsi Wang Kuan-Ching Li Ssu-Hsuan Lu Chun-Chieh Yang |
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Affiliation: | (1) Dept. of Computer Science and Information Management, Providence University, Shalu, Taichung, 43301, Taiwan;(2) Dept. of Computer Science and Information Engineering, Providence University, Shalu, Taichung, 43301, Taiwan |
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Abstract: | High speed networks and rapidly improving microprocessor performance make the network of workstations an extremely important
tool for parallel computing in order to speedup the execution of scientific applications. Shared memory is an attractive programming
model for designing parallel and distributed applications, where the programmer can focus on algorithmic development rather
than data partition and communication. Based on this important characteristic, the design of systems to provide the shared
memory abstraction on physically distributed memory machines has been developed, known as Distributed Shared Memory (DSM).
DSM is built using specific software to combine a number of computer hardware resources into one computing environment. Such
an environment not only provides an easy way to execute parallel applications, but also combines available computational resources
with the purpose of speeding up execution of these applications. DSM systems need to maintain data consistency in memory,
which usually leads to communication overhead. Therefore, there exists a number of strategies that can be used to overcome
this overhead issue and improve overall performance. Strategies as prefetching have been proven to show great performance
in DSM systems, since they can reduce data access communication latencies from remote nodes. On the other hand, these strategies
also transfer unnecessary prefetching pages to remote nodes. In this research paper, we focus on the access pattern during
execution of a parallel application, and then analyze the data type and behavior of parallel applications. We propose an adaptive
data classification scheme to improve prefetching strategy with the goal to improve overall performance. Adaptive data classification
scheme classifies data according to the accessing sequence of pages, so that the home node uses past history access patterns
of remote nodes to decide whether it needs to transfer related pages to remote nodes. From experimental results, we can observe
that our proposed method can increase the accuracy of data access in effective prefetch strategy by reducing the number of
page faults and misprefetching. Experimental results using our proposed classification scheme show a performance improvement
of about 9–25% over the same benchmark applications running on top of an original JIAJIA DSM system.
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Keywords: | Distributed shared memory Adaptive data classification scheme Effective prefetch strategy |
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