| 摘要: |
| 大规模并行计算是当前该领域研究的一大热点.由于大多数应用问题是数据并行问题,所以人们更多地采用数据并行计算方法来解决实际问题.在数据并行计算中,影响计算速度的一个重要因素是数据的划分状况.该文针对一种较为流行的面向对象数据并行语言——pC++的数据划分算法进行了分析,并指出了其不足之处,同时提出了一种改进的数据划分算法.实验表明,此算法与原有算法相比具有明显的优越性. |
| 关键词: 大规模并行计算,数据并行,面向对象,pC++,数据划分算法. |
| DOI： |
| 分类号: |
| 基金项目:本文研究得到国防科工委“九五”预研基金资助. |
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| Research and Improvement on the Data Distribution Algorithm of pC++ Language |
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SHI Wei,FANG Bin-xing,HU Ming-zeng
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| Abstract: |
| Large-scale parallel computing is a hot spot of current research. Because most of the scientific calculation is data parallel calculation, people would like to solve real problems by means of data parallelism. As for data parallel calculation, one of the critical factors that influence the running performance is the status of data distribution. In this paper, the authors analyze the data distribution algorithm of a prevalent object-oriented data parallel language——pC++ and point out the weaknesses of it. Then they present an improved algorithm. The results of the experiment show that it is superior to the former algorithm. |
| Key words: Large-scale parallel computing, data parallel, object-oriented, pC++, data distribution algorithm. |
