Solving tridiagonal systems on a GPU

Abstract

We implement a parallel tridiagonal solver based on cyclic reduction (CR) for a graphics processing unit (GPU). The bane of such solvers is a low computation to communication ratio. With this our main consideration we focus our effort on lowering communication costs. In so doing we accelerate system solving. Further, in the diagonally dominant case computation is decoupled into independent partitions allowing for efficient processing of larger systems.