Prefetching transfers a data item in advance from its storage location to its usage location so that communication is hidden and does not delay computation. We present a novel prefetching technique for object-based Distributed Shared Memory (DSM) systems and discuss its implementation. In contrast to page-based DSMs, an object-based DSM distributes data on the level of objects, rendering current prefetchers for page-based DSMs unsuitable due to more complex data streams. To predict future data accesses, our prefetcher uses a new predictor (Esodyp+) based on a modified Markov model that automatically adapts to program behavior. We compare our prefetching strategy with both a stride prefetcher and the prefetcher of the Delphi DSM system. For several benchmarks our prefetching strategy reduces the number of network messages by about 60 %. On 8 nodes, runtime is reduced by 15 % on average. Hence, network-bound programs benefit from our solution, In contrast to the other predictors, Esodyp+ achieves a prediction accuracy above 80 % with only 8 % of unused prefetches for the benchmarks. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Klemm, M., Beyler, J. C., Lampert, R. T., Philippsen, M., & Clauss, P. (2007). Esodyp+: Prefetching in the Jackal Software DSM. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4641 LNCS, pp. 563–573). Springer Verlag. https://doi.org/10.1007/978-3-540-74466-5_60
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