A Generalized Framework for Auto-tuning Stencil Computations

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This work introduces a generalized framework for automatically tuning stencil computations to achieve superior performance on a broad range of multicore architectures. Stencil (nearest-neighbor) based kernels constitute the core of many important scientific applications involving block-structured grids. Auto-tuning systems search over optimization strategies to find the combination of tunable parameters that maximizes computational efficiency for a given algorithmic kernel. Although the auto-tuning strategy has been successfully applied to libraries, generalized stencil kernels are not amenable to packaging as libraries. Studied kernels in this work include both memory-bound kernels as well as a computation-bound bilateral filtering kernel. We introduce a generalized ... continued below

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Kamil, Shoaib; Chan, Cy; Williams, Samuel; Oliker, Leonid; Shalf, John; Howison, Mark et al. May 1, 2009.

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This work introduces a generalized framework for automatically tuning stencil computations to achieve superior performance on a broad range of multicore architectures. Stencil (nearest-neighbor) based kernels constitute the core of many important scientific applications involving block-structured grids. Auto-tuning systems search over optimization strategies to find the combination of tunable parameters that maximizes computational efficiency for a given algorithmic kernel. Although the auto-tuning strategy has been successfully applied to libraries, generalized stencil kernels are not amenable to packaging as libraries. Studied kernels in this work include both memory-bound kernels as well as a computation-bound bilateral filtering kernel. We introduce a generalized stencil auto-tuning framework that takes a straightforward Fortran expression of a stencil kernel and automatically generates tuned implementations of the kernel in C or Fortran to achieve performance portability across diverse computer architectures.

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  • Cray User Group Conference 2009, Atlanta, GA, 5/4/2009 to 5/7/2009

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  • Report No.: LBNL-2078E
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 962935
  • Archival Resource Key: ark:/67531/metadc926963

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  • May 1, 2009

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  • Nov. 13, 2016, 7:26 p.m.

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  • Nov. 18, 2016, 2:45 p.m.

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Kamil, Shoaib; Chan, Cy; Williams, Samuel; Oliker, Leonid; Shalf, John; Howison, Mark et al. A Generalized Framework for Auto-tuning Stencil Computations, article, May 1, 2009; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc926963/: accessed September 23, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.