Boosting GPU Performance by Profiling-Based L1 Data Cache Bypassing

Abstract

Cache memories have been introduced in recent generations of Graphics Processing Units (GPUs) to benefit general-purpose computing on GPUs (GPGPUs). In this work, we analyze the memory access patterns of GPGPU applications and propose a cost-effective profiling-based method to identify the data accesses that should bypass the L1 data cache to improve performance. The evaluation indicates that the proposed L1 cache bypassing can improve the GPU performance by 13.8% on average.