Incorporating MAGMA into the 'fields' spatial statistics package

In this report we describe how to incorporate the Cholesky decomposition from the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library into some of the calculations of the 'fields' spatial statistics package in R. We provide MAGMA installation instructions as well as demonstrations of performance when applied to simulated datasets and the CO2 dataset available in fields. While there are other spatial statistics packages in R using parallelism, such as bigGP and parspatstat, none to our knowledge directly incorporates GPUs or other coprocessors.

Our code is timed on Caldera computational nodes in the National Center for Atmospheric Research's Yellowstone supercomputing environment. We find that for 40,000 x 40,000 matrices the MAGMA-accelerated decomposition has a 30.7 and 46.2 times speedup for 1 and 2 GPU implementations respectively over chol, the standard Cholesky decomposition function in R (with settings allowing R programmers to use our accelerated function like they would chol).