Year: 2009
Type: conference-paper
Abstract: ABSTRACT: 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. KEYWORDS: Multicore, XT4, Auto-tuning, Auto-parallelization 1
Authors: Shoaib Kamil, Cy Chan, Samuel Williams, Leonid Oliker, John Shalf, Mark Howison, E. Wes Bethel, Prabhat
Institution: Lawrence Berkeley National Laboratory
Language: English
Subfield: Hardware and Architecture
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1519701134