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Workshop on Job Scheduling Strategies for Parallel Processing

JSSPP 1995: Job Scheduling Strategies for Parallel Processing pp 70–91Cite as

Scheduling to reduce memory coherence overhead on coarse-grain multiprocessors

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 949))

Abstract

Some Distributed Shared Memory (DSM) and Cache-Only Memory Architecture (COMA) multiprocessors keep processes near the data they reference by transparently replicating remote data in the processes' local memories. This automatic replication of data can impose substantial memory system overhead on an application since all replicated data must be kept coherent. We examine the effect of task scheduling on data replication and memory system overhead due to coherency requirements. We show that simple policies using programmer hints can reduce memory coherence overhead in our workload applications.

This research was supported in part by NSF grant CCR-9113170.

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Authors and Affiliations

  1. Department of Computer Science, Duke University, 27708-0129, Durham, NC, USA

    Christopher Connelly & Caria Schlatter Ellis

Authors
  1. Christopher Connelly
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  2. Caria Schlatter Ellis
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Dror G. Feitelson Larry Rudolph

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© 1995 Springer-Verlag Berlin Heidelberg

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Connelly, C., Ellis, C.S. (1995). Scheduling to reduce memory coherence overhead on coarse-grain multiprocessors. In: Feitelson, D.G., Rudolph, L. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 1995. Lecture Notes in Computer Science, vol 949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60153-8_23

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  • DOI: https://doi.org/10.1007/3-540-60153-8_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60153-1

  • Online ISBN: 978-3-540-49459-1

  • eBook Packages: Springer Book Archive

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