Optimizing UPC programs for multi-core systems

被引：0
|
作者：
Zheng, Yili [1 ]
机构：
[1] Univ Calif Berkeley, Lawrence Berkeley Lab, Berkeley, CA 94720 USA
来源：
SCIENTIFIC PROGRAMMING | 2010年 / 18卷 / 3-4期
关键词：
UPC; PGAS;
D O I：
10.1155/2010/646829
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The Partitioned Global Address Space (PGAS) model of Unified Parallel C (UPC) can help users express and manage application data locality on non-uniform memory access (NUMA) multi-core shared-memory systems to get good performance. First, we describe several UPC program optimization techniques that are important to achieving good performance on NUMA multi-core computers with examples and quantitative performance results. Second, we use two numerical computing kernels, parallel matrix-matrix multiplication and parallel 3-D FFT, to demonstrate the end-to-end development and optimization for UPC applications. Our results show that the optimized UPC programs achieve very good and scalable performance on current multi-core systems and can even outperform vendor-optimized libraries in some cases.
引用
收藏
页码：183 / 191
页数：9
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