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OpenCL, along with CUDA, is one of the main tools used to program GPGPUs.However, it allows running the same code on multi-core CPUs too, making it arival for the long-established OpenMP. In this paper we compare OpenCL andOpenMP when developing and running compute-heavy code on a CPU. Both ease ofprogramming and performance aspects are considered. Since, unlike a GPU, nomemory copy operation is involved, our comparisons measure the code generationquality, as well as thread management efficiency of OpenCL and OpenMP. Weevaluate the performance of these development tools under two conditions: alarge number of short-running compute-heavy parallel code executions, when morethread management is performed, and a small number of long-running parallelcode executions, when less thread management is required. The results show thatOpenCL and OpenMP each win in one of the two conditions. We argue that whileusing OpenMP requires less setup, OpenCL can be a viable substitute for OpenMPfrom a performance point of view, especially when a high number of threadinvocations is required. We also provide a number of potential pitfalls towatch for when moving from OpenMP to OpenCL.

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming