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- W3128350060 abstract "High energy consumption is one of the biggest obstacles to the rapid development of computing systems, and reducing energy consumption is quite urgent and necessary for sustainable computing. Low-energy scheduling based on dynamic voltage and frequency scaling (DVFS) is one of the most commonly used energy optimization techniques. Recent survey works have reviewed some low-energy scheduling algorithms, but there is currently no systematic review in low-energy <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>parallel</i> scheduling algorithms. With the increasing complexity of function requirements, many parallel applications have been executed in various sustainable computing systems. In this paper, we survey recent advances in low-energy parallel scheduling algorithms according to three scheduling styles, namely: 1) energy-efficient parallel scheduling algorithms; 2) energy-aware parallel scheduling algorithms; and 3) energy-conscious parallel scheduling algorithms. Low-energy parallel scheduling algorithms basically involve five categories of 1) heuristic algorithms; 2) meta-heuristic algorithms; 3) integer programming algorithms; 4) machine learning algorithms; and 5) game theory algorithms. Further, we introduce the future trends in low-energy parallel scheduling algorithms from the perspectives of new requirements and future developments. By surveying the recent advances and introducing the future trends, we expect to provide researchers with a systematic reference and development directions in low-energy parallel scheduling for sustainable computing systems." @default.
- W3128350060 created "2021-02-15" @default.
- W3128350060 creator A5017198055 @default.
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- W3128350060 creator A5034516221 @default.
- W3128350060 creator A5087894632 @default.
- W3128350060 date "2022-01-01" @default.
- W3128350060 modified "2023-10-18" @default.
- W3128350060 title "A Survey of Low-Energy Parallel Scheduling Algorithms" @default.
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