This paper presents a new parallel algorithm for sparse matrix factorization. This algorithm uses subforest-to-subcube mapping instead of the subtree-to-subcube mapping of another recently introduced scheme by Gupta and Kumar [13]. Asymptotically, both formulations are equally scalable on a wide range of architectures and a wide variety of problems. But the subtree-to-subcube mapping of the earlier formulation causes signi cant load imbalance among processors, limiting overall e ciency andâ€¦Â CONTINUE READING