Modeling performance variation due to cache sharing

  • Authors:

  • Andreas Sandberg;Andreas Sembrant;Erik Hagersten;David Black-Schaffer

  • Affiliations:

  • Uppsala University, Department of Information Technology, P.O. Box 337, SE-751 05, Sweden;Uppsala University, Department of Information Technology, P.O. Box 337, SE-751 05, Sweden;Uppsala University, Department of Information Technology, P.O. Box 337, SE-751 05, Sweden;Uppsala University, Department of Information Technology, P.O. Box 337, SE-751 05, Sweden

  • Venue:
  • HPCA '13 Proceedings of the 2013 IEEE 19th International Symposium on High Performance Computer Architecture (HPCA)
  • Year:
  • 2013

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Abstract

Shared cache contention can cause significant variability in the performance of co-running applications from run to run. This variability arises from different overlappings of the applications' phases, which can be the result of offsets in application start times or other delays in the system. Understanding this variability is important for generating an accurate view of the expected impact of cache contention. However, variability effects are typically ignored due to the high overhead of modeling or simulating the many executions needed to expose them.