Identifying performance bottlenecks on modern microarchitectures using an adaptable probe

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The gap between peak and delivered performance for scientific applications running on microprocessor-based systems has grown considerably in recent years. The inability to achieve the desired performance even on a single processor is often attributed to an inadequate memory system, but without identification or quantification of a specific bottleneck. In this work, we use an adaptable synthetic benchmark to isolate application characteristics that cause a significant drop in performance, giving application programmers and architects information about possible optimizations. Our adaptable probe, called sqmat, uses only four parameters to capture key characteristics of scientific workloads: working-set size, computational intensity, indirection, and ... continued below

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Griem, Gorden; Oliker, Leonid; Shalf, John & Yelick, Katherine January 20, 2004.

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The gap between peak and delivered performance for scientific applications running on microprocessor-based systems has grown considerably in recent years. The inability to achieve the desired performance even on a single processor is often attributed to an inadequate memory system, but without identification or quantification of a specific bottleneck. In this work, we use an adaptable synthetic benchmark to isolate application characteristics that cause a significant drop in performance, giving application programmers and architects information about possible optimizations. Our adaptable probe, called sqmat, uses only four parameters to capture key characteristics of scientific workloads: working-set size, computational intensity, indirection, and irregularity. This paper describes the implementation of sqmat and uses its tunable parameters to evaluate four leading 64-bit microprocessors that are popular building blocks for current high performance systems: Intel Itanium2, AMD Opteron, IBM Power3, and IBM Power4.

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OSTI as DE00828731

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  • 3rd International Workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems, Santa Fe, NM (US), 04/2004

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  • Report No.: LBNL--54901
  • Grant Number: AC03-76SF00098
  • Office of Scientific & Technical Information Report Number: 828731
  • Archival Resource Key: ark:/67531/metadc786215

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Office of Scientific & Technical Information Technical Reports

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  • January 20, 2004

Added to The UNT Digital Library

  • Dec. 3, 2015, 9:30 a.m.

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  • April 4, 2016, 1:11 p.m.

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Griem, Gorden; Oliker, Leonid; Shalf, John & Yelick, Katherine. Identifying performance bottlenecks on modern microarchitectures using an adaptable probe, article, January 20, 2004; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc786215/: accessed October 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.