Multitasking workload scheduling on flexible-core chip multiprocessors

  • Authors:
  • Divya P. Gulati;Changkyu Kim;Simha Sethumadhavan;Stephen W. Keckler;Doug Burger

  • Affiliations:
  • University of Texas at Austin, Austin, TX, USA;Intel Corporation, Santa Clara, CA, USA;Columbia University, New York, NY, USA;University of Texas at Austin, Austin, TX, USA;University of Texas at Austin, Austin, TX, USA

  • Venue:
  • Proceedings of the 17th international conference on Parallel architectures and compilation techniques
  • Year:
  • 2008

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Abstract

While technology trends have ushered in the age of chip multiprocessors (CMP), a fundamental question is what size to make each core. Most current commercial designs are symmetric CMPs (SCMP) in which each core is identical and range from a simple RISC processor to a complex out-of-order x86 processor. Some researchers have proposed asymmetric CMPs (ACMP) consisting of multiple types of cores. While less of an issue for ACMPs, the fixed nature of both these architectures makes them vulnerable to mismatches between the granularity of the cores and the parallelism in the workload, which can cause inefficient execution. To remedy this weakness, recent research has proposed flexible-core CMPs (FCMP), which have the capability of aggregating multiple small processing cores to form larger logical processors. FCMPs introduce a new resource allocation and scheduling problem which must determine how many logical processors should be configured, how powerful each processor should be, and where/when each task should run. This paper introduces and motivates this problem, describes the challenges associated with it, and evaluates algorithms appropriate for multitasking on FCMPs. We also evaluate static-core CMPs of various configurations and compare them to FCMPs for various multitasking workloads.