Performance analysis of massively parallel programs for graphics processing units

Abstract

Any modern Graphics Processing Unit (graphics card) is a good platform to run massively parallel programs. Still, we lack tools to observe and measure performance characteristics of GPU-based software. We state that due to complex memory hierarchy and thou- sands of execution threads the all performance issues are about efficient use of graphics card memory hierarchy. We propose to use GPGPUSim simulator, previously used mostly for graphics card architecture validation, for performance validation for CUDA-based program. We provide examples which show how to use the simulation for performance analysis of massively parallel programs.