Energy-efficient task scheduling for multi-core platforms with per-core DVFS
Energy-efficient task scheduling is a fundamental issue in many application domains, such as energy conservation for mobile devices and the operation of green computing data centers. Modern processors support dynamic voltage and frequency scaling (DVFS) on a per-core basis, i.e., the CPU can adjust...
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| Vydáno v: | Journal of parallel and distributed computing Ročník 86; s. 71 - 81 |
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| Jazyk: | angličtina |
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Elsevier Inc
01.12.2015
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| ISSN: | 0743-7315, 1096-0848 |
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| Abstract | Energy-efficient task scheduling is a fundamental issue in many application domains, such as energy conservation for mobile devices and the operation of green computing data centers. Modern processors support dynamic voltage and frequency scaling (DVFS) on a per-core basis, i.e., the CPU can adjust the voltage or frequency of each core. As a result, the core in a processor may have different computing power and energy consumption. To conserve energy in multi-core platforms, we propose task scheduling algorithms that leverage per-core DVFS and achieve a balance between performance and energy consumption. We consider two task execution modes: the batch mode, which runs jobs in batches; and the online mode in which jobs with different time constraints, arrival times, and computation workloads co-exist in the system.
For tasks executed in the batch mode, we propose an algorithm that finds the optimal scheduling policy; and for the online mode, we present a heuristic algorithm that determines the execution order and processing speed of tasks in an online fashion. The heuristic ensures that the total cost is minimal for every time interval during a task’s execution. Furthermore, we analyze and derive algorithms with low time complexity for each mode.
•We propose task scheduling algorithms that leverage per-core DVFS on multi-cores.•Solve task-to-core, execution order, and the core frequency of task simultaneously.•For batch mode, our algorithm finds the optimal scheduling plan.•For online mode, our heuristic achieves a balance between performance and energy. |
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| AbstractList | Energy-efficient task scheduling is a fundamental issue in many application domains, such as energy conservation for mobile devices and the operation of green computing data centers. Modern processors support dynamic voltage and frequency scaling (DVFS) on a per-core basis, i.e., the CPU can adjust the voltage or frequency of each core. As a result, the core in a processor may have different computing power and energy consumption. To conserve energy in multi-core platforms, we propose task scheduling algorithms that leverage per-core DVFS and achieve a balance between performance and energy consumption. We consider two task execution modes: the batch mode, which runs jobs in batches; and the online mode in which jobs with different time constraints, arrival times, and computation workloads co-exist in the system.
For tasks executed in the batch mode, we propose an algorithm that finds the optimal scheduling policy; and for the online mode, we present a heuristic algorithm that determines the execution order and processing speed of tasks in an online fashion. The heuristic ensures that the total cost is minimal for every time interval during a task’s execution. Furthermore, we analyze and derive algorithms with low time complexity for each mode.
•We propose task scheduling algorithms that leverage per-core DVFS on multi-cores.•Solve task-to-core, execution order, and the core frequency of task simultaneously.•For batch mode, our algorithm finds the optimal scheduling plan.•For online mode, our heuristic achieves a balance between performance and energy. Energy-efficient task scheduling is a fundamental issue in many application domains, such as energy conservation for mobile devices and the operation of green computing data centers. Modern processors support dynamic voltage and frequency scaling (DVFS) on a per-core basis, i.e., the CPU can adjust the voltage or frequency of each core. As a result, the core in a processor may have different computing power and energy consumption. To conserve energy in multi-core platforms, we propose task scheduling algorithms that leverage per-core DVFS and achieve a balance between performance and energy consumption. We consider two task execution modes: the batch mode, which runs jobs in batches; and the online mode in which jobs with different time constraints, arrival times, and computation workloads co-exist in the system. For tasks executed in the batch mode, we propose an algorithm that finds the optimal scheduling policy; and for the online mode, we present a heuristic algorithm that determines the execution order and processing speed of tasks in an online fashion. The heuristic ensures that the total cost is minimal for every time interval during a task's execution. Furthermore, we analyze and derive algorithms with low time complexity for each mode. |
| Author | Lin, Ching-Chi Wu, Jan-Jan Hsu, Wei-Te Cheng, Po-Wen Chang, Chao-Jui Syu, You-Cheng Liu, Pangfeng |
| Author_xml | – sequence: 1 givenname: Ching-Chi surname: Lin fullname: Lin, Ching-Chi email: deathsimon@iis.sinica.edu.tw organization: 11529 128, Section 2, Academia Road, Nankang, Taipei, Taiwan – sequence: 2 givenname: You-Cheng surname: Syu fullname: Syu, You-Cheng email: arosusti@gmail.com organization: 10617 1, Section 4, Roosevelt Road, Taipei, Taiwan – sequence: 3 givenname: Chao-Jui orcidid: 0000-0002-9281-4145 surname: Chang fullname: Chang, Chao-Jui email: crchang@iis.sinica.edu.tw organization: 11529 128, Section 2, Academia Road, Nankang, Taipei, Taiwan – sequence: 4 givenname: Jan-Jan surname: Wu fullname: Wu, Jan-Jan email: wuj@iis.sinica.edu.tw organization: 11529 128, Section 2, Academia Road, Nankang, Taipei, Taiwan – sequence: 5 givenname: Pangfeng surname: Liu fullname: Liu, Pangfeng email: pangfeng@csie.ntu.edu.tw organization: 10617 1, Section 4, Roosevelt Road, Taipei, Taiwan – sequence: 6 givenname: Po-Wen surname: Cheng fullname: Cheng, Po-Wen email: sting@itri.org.tw organization: 31040 195, Section 4, Chung Hsing Road, Chutung, Hsinchu, Taiwan – sequence: 7 givenname: Wei-Te surname: Hsu fullname: Hsu, Wei-Te email: victor.hsu@itri.org.tw organization: 31040 195, Section 4, Chung Hsing Road, Chutung, Hsinchu, Taiwan |
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| Cites_doi | 10.1007/s11227-010-0416-0 10.1145/1206035.1206038 10.1016/j.jpdc.2012.03.005 10.1016/j.future.2013.06.009 10.1145/1290672.1290686 10.1109/DATE.2011.5763052 10.1109/ICPP.2014.47 10.1016/0020-0190(79)90117-0 10.1145/1529255.1529260 10.1109/DATE.2011.5763190 10.1002/cpe.2889 10.1145/2539036.2539049 10.1006/jpdc.2000.1714 10.1109/TPDS.2011.87 |
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| SubjectTerms | Algorithms Computation DVFS Electric potential Energy consumption Energy-efficient Multi-core Online Processors Task characteristics Task scheduling Tasks |
| Title | Energy-efficient task scheduling for multi-core platforms with per-core DVFS |
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