Design and Implementation of an Agent Home Scheme Strategy for Prefetch-Based DSM Systems |
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Authors: | Hsiao-Hsi Wang Kuan-Ching Li Ssu-Hsuan Lu Chun-Chieh Yang Jean-Luc Gaudiot |
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Affiliation: | (1) Department of Computer Science and Information Management, Providence University, Shalu, Taichung, 43301, Taiwan, ROC;(2) Department of Computer Science and Information Engineering, Providence University, Shalu, Taichung, 43301, Taiwan, ROC;(3) Department of Electrical Engineering and Computer Science, University of California—Irvine, Irvine, CA 92697, USA |
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Abstract: | In recent years, cluster computing has been widely investigated and there is no doubt that it can provide a cost-effective
computing infrastructure by aggregating computational power, communication, and storage resources. Moreover, it is also considered
to be a very attractive platform for low-cost supercomputing. Distributed shared memory (DSM) systems utilize the physical
memory of each computing node interconnected in a private network to form a global virtual shared memory. Since this global
shared memory is distributed among the computing nodes, accessing the data located in remote computing nodes is an absolute
necessity. However, this action will result in significant remote memory access latencies which are major sources of overhead
in DSM systems. For these reasons, in order to increase overall system performance and decrease this overhead, a number of
strategies have been devised. Prefetching is one such approach which can reduce latencies, although it always increases the
workload in the home nodes. In this paper, we propose a scheme named Agent Home Scheme. Its most noticeable feature, when compared to other schemes, is that the agent home distributes the workloads of each computing
nodes when sending data. By doing this, we can reduce not only the workload of the home nodes by balancing the workload for
each node, but also the waiting time. Experimental results show that the proposed method can obtain about 20% higher performance
than the original JIAJIA, about 18% more than History Prefetching Strategy (HPS), and about 10% higher than Effective Prefetch
Strategy (EPS). |
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Keywords: | DSM systems Prefetching strategy Home-based Cluster computing |
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