Total Energy Minimization of Real-Time Tasks in an On-Chip Multiprocessor Using Dynamic Voltage Scaling Efficiency Metric

Kim, Hyun‐Jin; Hong, Hyejeong; Kim, Hong-Sik; Ahn, Jin-Ho; Kang, Sungho

doi:10.1109/tcad.2008.2006094

Cited by 19 publications

(10 citation statements)

References 15 publications

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“…The unused cores are powered off to save energy [9,10]. Core processing speed is proportional to the supplied clock frequency.…”

Section: Processor Modelmentioning

confidence: 99%

“…The single-core scheduling [3][4][5][7][8][9][10] executes the real-time task on a single core and turns off the power of the other cores. The all-cores scheduling [13] executes the task on all available cores.…”

Section: ⅳ Evaluationmentioning

confidence: 99%

“…Numerous previous studies [3][4][5][7][8][9][10] have investigated the energy minimization of real-time tasks on multiple processing elements (PLs). However, they missed the rich energy-saving capability of parallel execution exploiting o verabundant PLs.…”

mentioning

confidence: 99%

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Energy-Efficient Multi- Core Scheduling for Real-Time Video Processing

백형구¹,

여정모²,

이완연³

2011

Journal of the Korea Society of Computer and Information

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In this paper, we propose an optimal scheduling scheme that minimizes the energy consumption of a real-time video task on the multi-core platform supporting dynamic voltage and frequency scaling. Exploiting parallel execution on multiple cores for less energy consumption, the propose scheme allocates an appropriate number of cores to the task execution, turns off the power of unused cores, and assigns the lowest clock frequency meeting the deadline. Our experiments show that the proposed scheme saves a significant amount of energy, up to 67% and 89% of energy consumed by two previous methods that execute the task on a single core and on all cores respectively.

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“…The unused cores are powered off to save energy [9,10]. Core processing speed is proportional to the supplied clock frequency.…”

Section: Processor Modelmentioning

confidence: 99%

Section: ⅳ Evaluationmentioning

confidence: 99%

See 1 more Smart Citation

Energy-Efficient Multi- Core Scheduling for Real-Time Video Processing

백형구¹,

여정모²,

이완연³

2011

Journal of the Korea Society of Computer and Information

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“…Second, EOTD algorithm implements the voltage scaling for each PE to minimize the energy consumption of task dependency graph. The previous research [21,22,30] separately research TA, TO and VS. They all implement VS based on TA and TO.…”

Section: Algorithm Frameworkmentioning

confidence: 99%

“…Most importantly, in the scheduling process, EOTD algorithm not only computes the communication energy, but also includes communication time into the scheduling time. As for the previous energy optimization scheduling algorithms of task dependency graph in multiprocessor environment, Papers [21,22,23] just consider the control dependency between tasks; Paper [24] takes only the communication energy into account, ignoring data transfer time; Papers [25,26] consider both communication time and communication energy, but they neglect the static energy of processing elements.…”

Section: Introductionmentioning

confidence: 99%

Energy-Optimization Scheduling of Task Dependent Graph on DVS-Enabled Cluster System

Gong

Zou³

2010

2010 Fifth Annual ChinaGrid Conference

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At present, power management in High-Performance Computing (HPC) environment is becoming a hot topic owning to its high operation cost, low reliability and environmental impact. In this paper, we investigate energy minimization scheduling algorithm of data dependent tasks in DVS-Enabled cluster system. Considering the data-intensive characteristics, the proposed EOTD (Energy Optimization scheduling for Task Dependent graph) algorithm adopts task clustering to reduce data transmission time and communication energy consumption. In order to decrease dynamic power of processing elements, it uses one of the power-saving techniques in system levelDynamic Voltage Scaling while not violating the deadline users specify. Moreover, on the premise that application execution is predictive and exclusive for processing elements, we employ Dynamic Power Management and Binary Search technique to reduce the static power of idle processing elements and last find the optimal number of processing elements. EOTD algorithm not only optimizes the energy consumption of task dependent graph, but also satisfies the QoS requirements service level agreement gives. Compared with VM and LJ-VM algorithm, experimental results demonstrate that EOTD algorithm can achieve larger energy optimization in less optimizing time.

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