Performance comparison of OpenCL and CUDA by benchmarking an optimized perspective backprojection

The increase in performance of Graphical Processing Units (GPUs) and the onward development of dedicated software tools within the last decade allows to transfer performance-demanding computations from the Central Processing Unit (CPU) to the GPU and to speed up certain tasks by utilizing the massiv parallel architecture of these devices. The Computate Unified Device Architecture (CUDA) developed by NVIDIA provides an easy hence effective way to develop application that target NVIDIA GPUs. It has become one of the cardinal software tools for this purpose. Recently the Open Computing Language (OpenCL) became available that is neither vendor-specific nor limited to GPUs only. As the benefits of CUDA-based image reconstruction are well known we aim at providing a comparison between the performance that can be achieved with CUDA in comparison to OpenCL by benchmarking the time required to perform a simple but computationally demanding task: the perspective backprojection. (orig.)