- Volume 14 Issue 3
DOI QR Code
Analysis on the GPU Performance according to Hierarchical Memory Organization
계층적 메모리 구성에 따른 GPU 성능 분석
- Received : 2013.11.14
- Accepted : 2013.12.26
- Published : 2014.03.28
Recently, GPGPU has been widely used for general-purpose processing as well as graphics processing by providing optimized hardware for parallel processing. Memory system has big effects on the performance of parallel processing units such as GPU. In the GPU, hierarchical memory architecture is implemented for high memory bandwidth. Moreover, both memory address coalescing and memory request merging techniques are widely used. This paper analyzes the GPU performance according to various memory organizations. According to our simulation results, GPU performance improves by 15.5%, 21.5%, 25.5%, 30.9% as adding 8KB L1, 16KB L1, 32KB L1, 64KB L1 cache, respectively, compared to case without L1 cache. However, experimental results show that some benchmarks decrease performance since memory transaction increases due to data dependency. Moreover, average memory access latency is increased as the depth of hierarchical cache level increases when cache miss occurs significantly.
GPU;Memory System;Hierarchical Memory Architecture;Memory Request Merging
Supported by : 한국연구재단, 정보통신산업진흥원
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