Algorithms for Computing the QR Decomposition of a Set of Matrices with Common Columns

The QR decomposition of a set of matrices which have common columns is investigated. The triangular factors of the QR decompositions are represented as nodes of a weighted directed graph. An edge between two nodes exists if and only if the columns of one of the matrices is a subset of the columns of the other. The weight of an edge denotes the computational complexity of deriving the triangular factor of the destination node from that of the source node. The problem is equivalent to constructing the graph and finding the minimum cost for visiting all the nodes. An algorithm which computes the QR decompositions by deriving the minimum spanning tree of the graph is proposed. Theoretical measures of complexity are derived and numerical results from the implementation of this and alternative heuristic algorithms are give

Greedy Givens algorithms for computing the rank-k updating of the QR decomposition

Abstract A Greedy Givens algorithm for computing the rank-1 updating of the QR decomposition is proposed. An exclusive-read exclusive-write parallel random access machine computational model is assumed. The complexity of the algorithms is calculated in two different ways. In the unlimited parallelism case a single time unit is required to apply a compound disjoint Givens rotation of any size. In the limited parallelism case all the disjoint Givens rotations can be applied simultaneously, but one time unit is required to apply a rotation to a two-element vector. The proposed Greedy algorithm requires approximately 5=8 the number of steps performed by the conventional sequential Givens rank-1 algorithm under unlimited parallelism. A parallel implementation of the sequential Givens algorithm outperforms the Greedy one under limited parallelism. An adaptation of the Greedy algorithm to compute the rank-k updating of the QR decomposition has been developed. This algorithm outperforms a recently reported parallel method for small k, but its efficiency decreases as k increases

Parallel strategies for rank-k updating of the qr decomposition

arallel strategies based on Givens rotations are proposed for updating the QR decomposition of an n × n matrix after a rank-k change (k < n). The complexity analyses of the Givens algorithms are based on the total number of Givens rotations applied to a 2-element vector. The algorithms, which are extensions of the rank-1 updating method, achieve the updating using approximately 2(k + n) compound disjoint Givens rotations (CDGRs) with elements annihilated by rotations in adjacent planes. Block generalization of the serial rank-1 algorithms are also presented. The algorithms are rich in level 3 BLAS operations, making them suitable for implementation on large scale parallel systems. The performance of some of the algorithms on a 2-D SIMD (single instruction stream-multiple instruction stream) array processor is discussed