ANALYSIS OF DIFFERENT PARTITIONING SCHEMES FOR PARALLEL GRAM-SCHMIDT ALGORITHMS

S. Oliveira, L. Borges, M. Holzrichter, T. Soma
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引用次数: 10

Abstract

In this paper we analyze implementations of parallel Gram-Schmidt orthogonalization algorithms. One of the first parallel orthogonalization of Gram-Schmidt was the row-wise partitioning of O'Leary and Whitman. In this paper we describe a pipelined implementation which uses column-wise partitioning schemes. Timing models for the column-wise parallel algorithms are derived. We compare our column-wise partitionings against the row-wise partitioning and validate our study with computational results. The pipelined orthogonalization algorithm is important because the timing analysis is independent of the architecture model. Threshold values of m max, which is the number of rows where row partitioning becomes better than column partitioning are found theoretically and verified with our experiments
并行gram-schmidt算法的不同划分方案分析
本文分析了并行Gram-Schmidt正交化算法的实现。Gram-Schmidt的第一个平行正交化是O'Leary和Whitman的逐行划分。在本文中,我们描述了一个使用列分区方案的流水线实现。推导了列并行算法的时序模型。我们比较了列分区和行分区,并用计算结果验证了我们的研究。流水线正交化算法非常重要,因为时序分析与体系结构模型无关。从理论上找到了mmax的阈值,即行分区优于列分区的行数,并通过我们的实验进行了验证
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