Efficient multicore-aware parallelization strategies for iterative stencil computations

Abstract

Stencil computations consume a major part of runtime in many scientific simulation codes. As prototypes for this class of algorithms we consider the iterative Jacobi and Gauss-Seidel smoothers and aim at highly efficient parallel implementations for cache-based multicore architectures. Temporal cache blocking is a known advanced optimization technique, which can reduce the pressure on the memory bus significantly. We apply and refine this optimization for a recently presented temporal blocking strategy designed to explicitly utilize multicore characteristics. Especially for the case of Gauss-Seidel smoothers we show that simultaneous multi-threading (SMT) can yield substantial performance improvements for our optimized algorithm.

15 pages, 10 figures

References in corpus (3)

• LIKWID: Lightweight Performance Tools
• Multicore-aware parallel temporal blocking of stencil codes for shared and distributed memory
• Introducing a Performance Model for Bandwidth-Limited Loop Kernels

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• LIKWID: A lightweight performance-oriented tool suite for x86 multicore environments
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• Tight Bounds for Low Dimensional Star Stencils in the Parallel External Memory Model