Title: Graphics Memory Bandwidth 증가에 따른 GPGPU 성능 향상 분석
Abstract: Graphic Processing Unit (GPU) has been highly hailed as a general-purpose (GP) high-performance computing unit in a wide variety of domains due to its high-computational capability and energy efficiency in comparison with CPU. Introducing High Bandwidth Memory (HBM), which will overcome the memory bandwidth wall within the context of GDDR5, to GPU is scheduled to take place soon. However, actual study on the impact of increased memory bandwidth on the performance of GPU with real GPGPU workloads is still lacking. We used a cycle accurate GPU simulator, GPGPU-Sim, to analyze the memory bandwidth sensitivity on 18 workloads from GPGPU benchmarks such as NVIDIA CUDA SDK, Rodina, and Parboil, and GPGPU-sim. Our results show most of GPU workloads from aforementioned benchmarks has low memory bandwidth sensitivity (x 1.16@ x 2BW, x 1.25@ x 4BW), yet several workloads have significant speedup with increased memory bandwidth. In addition, it is found that correlation between memory bandwidth sensitivity and memory intensiveness across the workloads used in the experiment is small (r=0.0817).
Publication Year: 2015
Publication Date: 2015-06-01
Language: en
Type: article
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