Intelligent Policy Selection for GPU Warp Scheduler

Lih Yih Chiou, Tsung Han Yang, Jian Tang Syu, Che Pin Chang, Yeong Jar Chang

研究成果: Conference contribution

摘要

The graphics processing unit (GPU) is widely used in applications that require massive computing resources such as big data, machine learning, computer vision, etc. As the diversity of applications grows, the GPU's performance becomes difficult to maintain by its warp scheduler. Most of the prior studies of the warp scheduler are based on static analysis of GPU hardware behavior for certain types of benchmarks. We propose for the first time (to the best of our knowledge), a machine learning approach to intelligently select suitable policies for various applications in runtime. The simulation results indicate that the proposed approach can maintain performance comparable to the best policy across different applications.

原文English
主出版物標題Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
發行者Institute of Electrical and Electronics Engineers Inc.
頁面302-303
頁數2
ISBN(電子)9781538678848
DOIs
出版狀態Published - 2019 三月
事件1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019 - Hsinchu, Taiwan
持續時間: 2019 三月 182019 三月 20

出版系列

名字Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019

Conference

Conference1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
國家/地區Taiwan
城市Hsinchu
期間19-03-1819-03-20

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 硬體和架構
  • 電氣與電子工程

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