Prefetch-aware shared resource management for multi-core systems

  • Authors:

  • Eiman Ebrahimi;Chang Joo Lee;Onur Mutlu;Yale N. Patt

  • Affiliations:

  • The University of Texas at Austin, Austin, TX, USA;Intel Corporation, Austin, TX, USA;Carnegie Mellon University, Pittsburgh, PA, USA;The University of Texas at Austin, Austin, TX, USA

  • Venue:
  • Proceedings of the 38th annual international symposium on Computer architecture
  • Year:
  • 2011

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Abstract

Chip multiprocessors (CMPs) share a large portion of the memory subsystem among multiple cores. Recent proposals have addressed high-performance and fair management of these shared resources; however, none of them take into account prefetch requests. Without prefetching, significant performance is lost, which is why existing systems prefetch. By not taking into account prefetch requests, recent shared-resource management proposals often significantly degrade both performance and fairness, rather than improve them in the presence of prefetching. This paper is the first to propose mechanisms that both manage the shared resources of a multi-core chip to obtain high-performance and fairness, and also exploit prefetching. We apply our proposed mechanisms to two resource-based management techniques for memory scheduling and one source-throttling-based management technique for the entire shared memory system. We show that our mechanisms improve the performance of a 4-core system that uses network fair queuing, parallelism-aware batch scheduling, and fairness via source throttling by 11.0%, 10.9%, and 11.3% respectively, while also significantly improving fairness.