SIGMA: a simulator infrastructure to guide memory analysis

  • Authors:
  • Luiz DeRose;K. Ekanadham;Jeffrey K. Hollingsworth;Simone Sbaraglia

  • Affiliations:
  • IBM T.J. Watson Research Center, Yorktown Heights, NY;IBM T.J. Watson Research Center, Yorktown Heights, NY;University of Maryland, College Park, MD;University of Rome, "La Sapienza", Rome, Italy

  • Venue:
  • Proceedings of the 2002 ACM/IEEE conference on Supercomputing
  • Year:
  • 2002

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Abstract

In this paper we present SIGMA (Simulation Infrastructure to Guide Memory Analysis), a new data collection framework and family of cache analysis tools. The SIGMA environment provides detailed cache information by gathering memory reference data using software-based instrumentation. This infrastructure can facilitate quick probing into the factors that influence the performance of an application by highlighting bottleneck scenarios including: excessive cache/TLB misses and inefficient data layouts. The tool can also assist in perturbation analysis to determine performance variations caused by changes to architecture or program. Our validation tests using the SPEC Swim benchmark show that most of the performance metrics obtained with SIGMA are within 1% of the metrics obtained with hardware performance counters, with the advantage that SIGMA provides performance data on a data structure level, as specified by the programmer.