The limits and effectiveness of data prefetching on scalable multiprocessors

Prefetching is a promising technique for hiding and tolerating the large memory latencies expected in scalable multiprocessors. In this paper we present and validate an analytical performance model for software-controlled data prefetching. The model incorporates all the important aspects affecting t...

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Vydané v:Performance evaluation Ročník 27; s. 209 - 229
Hlavní autori: Mao, Weihua, Saavedra, Rafael H.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 1996
Predmet:
Analytical modelling
Distributed shared-memory multiprocessors
Execution-driven simulation
Software data prefetching
Execution-driven simulation
Software data prefetching
Analytical modelling
Distributed shared-memory multiprocessors
ISSN:0166-5316, 1872-745X
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Popis
Shrnutí:Prefetching is a promising technique for hiding and tolerating the large memory latencies expected in scalable multiprocessors. In this paper we present and validate an analytical performance model for software-controlled data prefetching. The model incorporates all the important aspects affecting the performance of prefetching such as: program behavior, network topology, cache coherency protocols, memory consistency models, etc. We use execution-driven simulation to validate the predictions of the model with respect to overall speedup, average memory latency, and cache pollution. We show that the model provides accurate predictions for programs that do not saturate the bandwidth of the network. The model could be used by compilers and/or programmers to determine when to issue prefetch instructions in order to maximize the speedup that can be obtained from software-controlled prefetching.
ISSN:0166-5316
1872-745X
DOI:10.1016/S0166-5316(96)90028-0