Title :
Boosting GPU Performance by Profiling-Based L1 Data Cache Bypassing
Author :
Yijie Huangfu ; Wei Zhang
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.
Keywords :
cache storage; graphics processing units; GPGPU; GPU performance; GPU performance improvement; cache memories; cost-effective profiling-based method; data access identification; general-purpose computing-on-GPU; graphics processing units; memory access pattern analysis; profiling-based L1 data cache bypassing; Bandwidth; Benchmark testing; Graphics processing units; Instruction sets; Kernel; Pollution; System-on-chip;
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on
Conference_Location :
Shenzhen
DOI :
10.1109/CCGrid.2015.67