Speaker
Description
Mixed precision computation has attracted great attention in recent years partly due to the evolution of machine learning and hardware infrastructure. Recent development on mixed precision algorithms has largely enhanced the performance of various linear algebra solvers. In this talk, we propose a mixed precision algorithm for the computation of matrix root functions, primarily the matrix square root and other higher order roots. We introduce a new refinement framework that is capable of refining the lower precision solution to the working precision level. We show that carefully designed mixed precision algorithms compute the matrix root functions to full working precision accuracy and offer speedup in most scenarios compared to the fixed precision method.