Instruction Prefetch for Improving GPGPU Performance

DOI Web Site 参考文献19件
  • CAO Jianli
    School of Software Technology, Dalian University of Technology
  • CHEN Zhikui
    School of Software Technology, Dalian University of Technology
  • WANG Yuxin
    School of Computer Science and Technology, Dalian University of Technology
  • GUO He
    School of Software Technology, Dalian University of Technology
  • WANG Pengcheng
    Jianghuai College of Ahui University

抄録

<p>Like many processors, GPGPU suffers from memory wall. The traditional solution for this issue is to use efficient schedulers to hide long memory access latency or use data prefetch mech-anism to reduce the latency caused by data transfer. In this paper, we study the instruction fetch stage of GPU's pipeline and analyze the relationship between the capacity of GPU kernel and instruction miss rate. We improve the next line prefetch mechanism to fit the SIMT model of GPU and determine the optimal parameters of prefetch mechanism on GPU through experiments. The experimental result shows that the prefetch mechanism can achieve 12.17% performance improvement on average. Compared with the solution of enlarging I-Cache, prefetch mechanism has the advantages of more beneficiaries and lower cost.</p>

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