Abstract
The clusters of SMP using fast networks, such as the Myricom’s Myrinet, have emerged as important platforms for high performance computing. Although their peak advertised performance is very high, their real performance may be much lower than the peak advertised performance for many applications. To achieve high performance, we need to take advantages of both SMP and cluster architectures. Based on the HPM model for parallel computing, the performance of clusters of SMP systems is analyzed, and principles to optimize parallel algorithms (both from the parallelism and locality point of view) are proposed. The influence of memory hierarchies on the performance is highly emphasized. Some practical examples on commercial clusters of SMPs systems Dawning D2000-2 and D3000 are also given.
Supported by the National Natural Science Foundation of China (Grand 69933020)
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© 2002 Springer-Verlag Berlin Heidelberg
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Qiao, X. (2002). Optimization of Parallel Algorithms on Cluster of SMP’s. In: Fagerholm, J., Haataja, J., Järvinen, J., Lyly, M., Råback, P., Savolainen, V. (eds) Applied Parallel Computing. PARA 2002. Lecture Notes in Computer Science, vol 2367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48051-X_49
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DOI: https://doi.org/10.1007/3-540-48051-X_49
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