  Although the performance of commodity computers has improved drastically with
the introduction of multicore processors and GPU computing, the standard R
distribution is still based on single-threaded model of computation, using only
a small fraction of the computational power available now for most desktops and
laptops. Modern statistical software packages rely on high performance
implementations of the linear algebra routines there are at the core of several
important leading edge statistical methods. In this paper we present a GPU
implementation of the GMRES iterative method for solving linear systems. We
compare the performance of this implementation with a pure single threaded
version of the CPU. We also investigate the performance of our implementation
using different GPU packages available now for R such as gmatrix, gputools or
gpuR which are based on CUDA or OpenCL frameworks.
