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 ofmmax, which is the number of rows where row partitioning becomes better than column partitioning are found theoretically and verified with our experiments