Performance Tuning of Matrix Multiplication in OpenCL on Different GPUs and CPUs

OpenCL (Open Computing Language) is a framework for general-purpose parallel programming. Programs written in OpenCL are functionally portable across multiple processors including CPUs, GPUs, and also FPGAs. Using an auto-tuning technique makes performance of OpenCL programs also portable on different processors. We have developed an auto-tuning system with a code generator for fast matrix multiply kernels in OpenCL. This paper presents results of performance evaluation of DGEMM (double-precision general matrix multiply) and SGEMM (single-precision GEMM) implementations by using the auto-tuning system. Performance evaluations are conducted on two AMD GPUs (Tahiti and Cayman), two NVIDIA GPUs (Kepler and Fermi), and two CPUs (Intel Sandy Bridge and AMD Bulldozer). Our GEMM implementations on the AMD GPUs show higher performance than the highly tuned vendor library while the implementations on the NVIDIA GPUs are comparable.