CHESS: Joint Energy and Makespan Optimization for Dynamic CNN Task Scheduling on the Heterogeneous System
Authors: 
Zimo Ma, Yifeng Li, Di Liu, Ziheng Zhang, Kuangyu ZhengAuthors Info & Claims
Pages 172 - 176
Abstract
In this paper, we investigate both the energy consumption and running time of different CNN tasks on GPUs or CPUs, and analyze their characterization for different CNN models under different application and system configuration factors. We find that this joint energy consumption and makespan optimization problem can be formulated as an integer linear programming problem. Then we propose CHESS (CNN-task Heterogeneous Efficient Scheduling System) with a two-stage heuristic scheduling algorithm, to better allocate computing resources for the upcoming tasks, and to schedule them dynamically on the heterogeneous cluster. Experiments show that our CHESS can save up to 15.9% energy and decrease up to 32.7% makespan over existing approaches.
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Published In
February 2023
619 pages
ISBN:9781450398411
DOI:10.1145/3587716
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 07 September 2023
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ICMLC 2023
ICMLC 2023: 2023 15th International Conference on Machine Learning and Computing
February 17 - 20, 2023
Zhuhai, China
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