Multi-core acceleration of chemical kinetics for simulation and prediction

Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis Pub Date : 2009-11-14 DOI:10.1145/1654059.1654067

J. C. Linford, J. Michalakes, Manish Vachharajani, Adrian Sandu

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引用次数: 58

Abstract

This work implements a computationally expensive chemical kinetics kernel from a large-scale community atmospheric model on three multi-core platforms: NVIDIA GPUs using CUDA, the Cell Broadband Engine, and Intel Quad-Core Xeon CPUs. A comparative performance analysis for each platform in double and single precision on coarse and fine grids is presented. Platform-specific design and optimization is discussed in a mechanism-agnostic way, permitting the optimization of many chemical mechanisms. The implementation of a three-stage Rosenbrock solver for SIMD architectures is discussed. When used as a template mechanism in the the Kinetic PreProcessor, the multi-core implementation enables the automatic optimization and porting of many chemical mechanisms on a variety of multi-core platforms. Speedups of 5.5x in single precision and 2.7x in double precision are observed when compared to eight Xeon cores. Compared to the serial implementation, the maximum observed speedup is 41.1x in single precision.

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用于模拟和预测的化学动力学多核加速

这项工作在三个多核平台上实现了一个计算昂贵的化学动力学内核，该内核来自一个大型社区大气模型:使用CUDA的NVIDIA gpu, Cell宽带引擎和英特尔四核Xeon cpu。对各平台在粗网格和细网格上的双精度和单精度性能进行了对比分析。平台特定的设计和优化以一种机制不可知的方式进行讨论，允许许多化学机制的优化。讨论了SIMD体系结构的三阶段Rosenbrock求解器的实现。当在Kinetic PreProcessor中用作模板机制时，多核实现可以在各种多核平台上自动优化和移植许多化学机制。与8个Xeon内核相比，单精度速度提高了5.5倍，双精度速度提高了2.7倍。与串行实现相比，单精度下观察到的最大加速是41.1倍。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis

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