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A critical issue in achieving the performance of data parallel programs is how to efficiently decompose data across processors. On distributed-memory machines, a good data decomposition should increase processor workload balance and reduce interprocessor communication. Data decomposition consists of data distribution and data alignment. In this paper, we propose a trapezoid data distribution pattern and new data alignment algorithms using alignment graph (AG). Our AG-based alignment framework is unique from other related work because it takes advantage of the effect of optimal expression evaluation with regard to multiple assignment statements.
Parallel Processing, 1994. Vol. 1. ICPP 1994. International Conference on (Volume:2 )
Date of Conference: 15-19 Aug. 1994