Accelerating Simulations in R using Automatically Generated GPGPU-Code
Frank Krämer, Andreas Leha, Tim Beißbarth · 2011
Newly developed classifiers, estimators, and other algorithms are often tested in simulations to assess power, control of alpha-level, accuracy and related quality criteria. Depending on the required number of simulation runs and the complexity of algorithms, especially the estimation of parameters and the drawing of random numbers under certain distributions, these simulations can run for several hours or even days. Such simulations are embarrassingly parallel and, therefore, benefit massively from parallelization. Not everyone has access to clusters or grids, though, but highly parallel graphics cards suitable for general purpose computing are installed in many computers. While there is a distinct number of maintained R-packages available (Eddelbuettel2011) that are able to interface with GPUs and allow the user to speed up computations, integrating