A task-to-processor mapping algorithm is described for computing the parallel multifrontal Cholesky factorization of irregular sparse problems on distributed-memory multiprocessors. The performance of the mapping algo...
详细信息
A task-to-processor mapping algorithm is described for computing the parallel multifrontal Cholesky factorization of irregular sparse problems on distributed-memory multiprocessors. The performance of the mapping algorithm is compared with the only general mapping algorithm previously reported. Using this mapping, the distributed multifrontal algorithm is nearly as efficient on a collection of problems with irregular sparsity structure as it is for the regular grid problems.
暂无评论