# Performances of Methods for Solving a Linear System of Equations in the Architecture of GPU Accelerator in Case of Small Matrices

## Keywords:

GPU accelerator, MAGMA, linear algebra operation, LU factorization, small matrix, performance, batched computation, Random Butterfly Transformation.## Abstract

The algebraic operations with a large number of small matrices are a very important issue in science. The solutions for linear system of equations with LU factorization are specific of the mentioned operations that have numerous applications of algebraic operations with small matrices. In this work we consider the performances of methods for solving linear system of equations with batched LU factorization for small complex matrices on the graphic processor NVIDIA K40c.The versions with Partial Pivoting, without Pivoting and Random Butterfly Transformations of batched LU factorization for small matrices are presented and shown, which of these versions is the effective one, in which case we achieve high performance.

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*Mathematical Problems of Computer Science*,

*46*, 59–65. Retrieved from http://mpcs.sci.am/index.php/mpcs/article/view/149

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