Accelerating sparse Cholesky factorization on GPUs

摘要

Sparse factorization is a fundamental tool in scientific computing. As the major component of a sparse direct solver, it represents the dominant computational cost for many analyses. For factorizations which involve sufficient dense math, the substantial computational capability provided by GPUs (Graphics Processing Units) can help alleviate this cost. However, for many other cases, the prevalence of small/irregular dense math and the relatively slow communication between the host and device over the PCIe bus, make it challenging to significantly accelerate sparse factorization using the GPU.