Accelerating 'fields' by revamping the Cholesky Decomposition

The acceleration is motivated by a) Its frequent use in key computations in the spatial statistics R 'fields' package, b) Major bottleneck in 'fields' package execution and c) Operations involving big matrices make it suitable for parallelization.

The Cholesky Decomposition was accelerated last summer using the MAGMA library. However, the performance of the accelerated version on multiple GPUs was observed to be unconventional - a) Execution time on multiple GPUs was higher in comparison to single GPU execution and b) Deep copy and in-place algorithms had opposite impacts on performance when executed on one and multiple GPUs. Our CPU and GPU profiling, conducted this summer, explains the unconventional behavior observed in the multi-GPU executions.