第141回

In this talk, I will present a new library for computing matrix functions, and will do my best to present it in a way that should be of interest to researchers from R-CCS’s many disciplines. Matrix functions have a number of applications including materials science, the solution of partial differential equations, and the study of real world networks. In this talk, I will review the theory of matrix functions, and discuss several methods of computation. Then I will present the parallelization strategy of our library, including the use of communication avoiding algorithms and task based parallelization. I will discuss usability considerations, including how to build a library in Fortran which can be called from many different programming languages. I will finish by presenting a number of different applications of this library, including quantum chemistry, social network analysis, search engine optimization, and the calculation of the eigendecomposition of a matrix.