Adaptive Software Prefetching in Scalable Multiprocessors Using Cache Information

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Scalable multiprocessors present special challenges to static software prefetching because on these systems the memory access latency is not completely determined at compile time. Furthermore, dynamic software prefetching cannot do much better because individual nodes on large-scale multiprocessors would tend to experience different remote memory delays over time. A fixed prefetch distance, even when computed at run-time, cannot perform well for the whole duration of a software pipeline. Here we present an adaptive scheme for software prefetching that makes it possible for nodes to dynamically change, not only the amount of prefetching, but the prefetch distance as well. We show how simple performance data collected by hardware monitors can allow programs to observe, evaluate and change their prefetching policies. Our results show that adaptive prefetching (APF) was capable of improving performance over static and dynamic prefetching by 10%60%. (C) 2001 Elsevier Science B.V. All rights reserved.
Publisher
Elsevier Science Bv
Issue Date
2001-08
Language
English
Article Type
Article
Keywords

PERFORMANCE

Citation

PARALLEL COMPUTING, v.27, no.9, pp.1173 - 1195

ISSN
0167-8191
URI
http://hdl.handle.net/10203/78729
Appears in Collection
RIMS Journal Papers
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