Real-Time Constrained Task Scheduling in 3D Chip Multiprocessor to Reduce Peak Temperature

2010 ◽  
Author(s):  
Jiayin Li ◽  
Meikang Qiu ◽  
Jianwei Niu ◽  
Tianzhou Chen ◽  
Yongxin Zhu
Keyword(s):  
Real Time ◽  
Task Scheduling ◽  
Peak Temperature ◽  
Chip Multiprocessor

Thermal-aware task scheduling in 3D chip multiprocessor with real-time constrained workloads

2013 ◽  
Vol 12 (2) ◽  
pp. 1-22 ◽  
Author(s):  
Jiayin Li ◽  
Meikang Qiu ◽  
Jian-Wei Niu ◽  
Laurence T. Yang ◽  
Yongxin Zhu ◽  
...  
Keyword(s):  
Real Time ◽  
Task Scheduling ◽  
Chip Multiprocessor

Thermal-Aware Task Scheduling for Energy Minimization in Heterogeneous Real-Time MPSoC Systems

2016 ◽  
Vol 35 (8) ◽  
pp. 1269-1282 ◽  
Author(s):  
Junlong Zhou ◽  
Tongquan Wei ◽  
Mingsong Chen ◽  
Jianming Yan ◽  
Xiaobo Sharon Hu ◽  
...  
Keyword(s):  
Real Time ◽  
Task Scheduling ◽  
Energy Minimization

Prepare: P owe r -Awar e A p proximate Re a l-time Task Scheduling for Ene r gy-Adaptiv e QoS Maximization

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-25
Author(s):  
Shounak Chakraborty ◽  
Sangeet Saha ◽  
Magnus Själander ◽  
Klaus Mcdonald-Maier
Keyword(s):  
Real Time ◽  
Task Scheduling ◽  
Processing Speed ◽  
Empirical Evaluation ◽  
Adaptive Mechanism ◽  
Approximate Computing ◽  
Thermal Safety ◽  
Time Task ◽  
Individual Task ◽  
The Individual

Achieving high result-accuracy in approximate computing (AC) based real-time applications without violating power constraints of the underlying hardware is a challenging problem. Execution of such AC real-time tasks can be divided into the execution of the mandatory part to obtain a result of acceptable quality, followed by a partial/complete execution of the optional part to improve accuracy of the initially obtained result within the given time-limit. However, enhancing result-accuracy at the cost of increased execution length might lead to deadline violations with higher energy usage. We propose Prepare , a novel hybrid offline-online approximate real-time task-scheduling approach, that first schedules AC-based tasks and determines operational processing speeds for each individual task constrained by system-wide power limit, deadline, and task-dependency. At runtime, by employing fine-grained DVFS, the energy-adaptive processing speed governing mechanism of Prepare reduces processing speed during each last level cache miss induced stall and scales up the processing speed once the stall finishes to a higher value than the predetermined one. To ensure on-chip thermal safety, this higher processing speed is maintained only for a short time-span after each stall, however, this reduces execution times of the individual task and generates slacks. Prepare exploits the slacks either to enhance result-accuracy of the tasks, or to improve thermal and energy efficiency of the underlying hardware, or both. With a 70 - 80% workload, Prepare offers 75% result-accuracy with its constrained scheduling, which is enhanced by 5.3% for our benchmark based evaluation of the online energy-adaptive mechanism on a 4-core based homogeneous chip multi-processor, while meeting the deadline constraint. Overall, while maintaining runtime thermal safety, Prepare reduces peak temperature by up to 8.6 °C for our baseline system. Our empirical evaluation shows that constrained scheduling of Prepare outperforms a state-of-the-art scheduling policy, whereas our runtime energy-adaptive mechanism surpasses two current DVFS based thermal management techniques.

Requirements for Static Task Scheduling in Real Time Embedded Systems

2001 ◽  
pp. 35-44
Author(s):  
Chun Wong ◽  
Filip Thoen ◽  
Francky Catthoor ◽  
Diederik Verkest
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Task Scheduling
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