ANALYSIS OF DIFFERENT PARTITIONING SCHEMES FOR PARALLEL GRAM-SCHMIDT ALGORITHMS

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