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We present the performance analysis of OpenCL kernels for three recently introduced many-core accelerator architectures: Intel Xeon Phi coprocessor and NVIDIA Kepler and Fermi GPUs. We use a case study of finite element numerical integration, a practically important and theoretically interesting algorithm used in scientific computing. We design a single parametrized kernel for all three architectures and test the performance obtained in numerical tests. We indicate possible further, architecture dependent, optimizations and draw conclusions on the performance portability for different accelerator architectures and OpenCL programming model.

OpenCL Performance Portability for Xeon Phi Coprocessor and NVIDIA GPUs: A Case Study of Finite Element Numerical Integration