TY - GEN
T1 - Energy-efficient scheduling for parallel real-time tasks based on level-packing
AU - Kong, Fanxin
AU - Guan, Nan
AU - Deng, Qingxu
AU - Yi, Wang
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2011
Y1 - 2011
N2 - While much work has addressed energy-efficient scheduling for sequential tasks where each task can run on only one processor at a time, little work has been done for parallel tasks where an individual task can be executed by multiple processors simultaneously. In this paper, we develop energy minimizing algorithms for parallel task systems with timing guarantees. For parallel tasks executed by a fixed number of processors, we first propose several heuristic algorithms based on level-packing for task scheduling, and then present a polynomial-time complexity energy minimizing algorithm which is optimal for any given level-packed task schedule. For parallel tasks that can run on a variable number of processors, we propose another polynomial-time complexity algorithm to determine the number of processors executing each task, task schedule and frequency assignment. To the best of our knowledge, this is the first work that addresses energy-efficient scheduling for parallel real-time tasks. Our simulation result shows that the proposed approach can significantly reduce the system energy consumption. © 2011 ACM.
AB - While much work has addressed energy-efficient scheduling for sequential tasks where each task can run on only one processor at a time, little work has been done for parallel tasks where an individual task can be executed by multiple processors simultaneously. In this paper, we develop energy minimizing algorithms for parallel task systems with timing guarantees. For parallel tasks executed by a fixed number of processors, we first propose several heuristic algorithms based on level-packing for task scheduling, and then present a polynomial-time complexity energy minimizing algorithm which is optimal for any given level-packed task schedule. For parallel tasks that can run on a variable number of processors, we propose another polynomial-time complexity algorithm to determine the number of processors executing each task, task schedule and frequency assignment. To the best of our knowledge, this is the first work that addresses energy-efficient scheduling for parallel real-time tasks. Our simulation result shows that the proposed approach can significantly reduce the system energy consumption. © 2011 ACM.
KW - dynamic voltage scaling
KW - energy-efficient scheduling
KW - level-packing
KW - parallel tasks
KW - real-time systems
UR - https://www.scopus.com/pages/publications/79959319591
UR - https://www.scopus.com/pages/publications/79959319591#tab=impact
U2 - 10.1145/1982185.1982326
DO - 10.1145/1982185.1982326
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781450301138
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 635
EP - 640
BT - 26th Annual ACM Symposium on Applied Computing, SAC 2011
T2 - 26th Annual ACM Symposium on Applied Computing, SAC 2011
Y2 - 21 March 2011 through 24 March 2011
ER -