SGEMM, MTIMES & CUBLAS performance on the GPU

ArrayFireBenchmarks, CUDA 5 Comments

AccelerEyes is focused on not only providing the most easy to use GPU programming platform for CUDA capable GPUs by leveraging the MATLAB® language, our engineering organization is always looking for ways to improve the performance of all areas in the Jacket platform. A case in point is some recent work with matrix multiplication, specifically (Single General Matrix Multiply) SGEMM, or MTIMES.  The Jacket 1.3 release was based on CUBLAS for matrix multiplication and given the importance of matrix multiplication to so many of our customers, we decided to find out if we could improve performance of the function. Update: The new MTIMES routine in Jacket 1.4 has improved sigificantly since these benchmarks of the Release Candidate were taken. Have …