Efficient cost evaluation for sparse multifrontal QR factorization

This paper considers the sparse multifrontal QR factorization. An efficient method to evaluate numbers of multiplicative operations in factorizing each frontal matrix is proposed. These numbers can be treated as the node costs of the corresponding elimination tree. This knowledge is very useful to improve performance of sparse QR factorization. For example, experiments conducted so far show that about 10% of the parallel execution time can be reduced.