Evaluation of Partitioning Methods for Stream Applications on a Heterogeneous Multi-core Processor Simulator

Kai, Zheng; Zhu, Yongxin; Xu, Jun

doi:10.1109/euc.2008.164

Cited by 1 publication

(2 citation statements)

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“…Reference [6] proposed a clustering framework, along with a flexible multi-purpose clustering algorithm that initiated task clustering at the functional level based on dynamic profiling information, to take full advantage of the multi-core processor efficiency. Zheng Kai [7] compared the performance between the functional partitioning and the partitioning by data for multimedia streaming application, and presents the solution how to achieve the lower power consumption and the better performance.…”

Section: Related Workmentioning

confidence: 99%

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A Novel Task Partitioning Method for Multi-core Processor Based-on Cohesion and Coupling

Jiang¹,

Zeng

2013

JCP

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Task partition is a NP-Hard problem on multi-core processor. To achieve a good MCT (maximum completion time) goal, this paper presents a novel task partitioning method for multi-core processor based on the cohesion and coupling properties of tasks. First, the relations between the cohesion and coupling are analyzed and the computation method of coupling cost based on cohesion is designed with the task scheduling requirements considered. Then, aiming to the problem that the MCT (maximum completion time) is different when the tasks' coupling is changed and the tasks are rescheduled during the task partitioning process, an evaluating method of MCT with the considering of task scheduling requirements is designed. Last, this paper compartmentalizes tasks based on the MCT to make it minimum. This method reduces the processing of the combinatorial optimization problem in task partitioning process, and builds the relation between task partition and task scheduling. The experimental results testify this method available.

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Section: Related Workmentioning

confidence: 99%

“…is the ET of task i , if task i In the light of the LETFS (Longest Executing Task First Scheduling) rule, the max ET of all subtasks can be computed as formula(7). average ET of all subtasks.…”

mentioning

confidence: 99%

A Novel Task Partitioning Method for Multi-core Processor Based-on Cohesion and Coupling

Jiang¹,

Zeng

2013

JCP

View full text Add to dashboard Cite

show abstract

Evaluation of Partitioning Methods for Stream Applications on a Heterogeneous Multi-core Processor Simulator

Cited by 1 publication

References 7 publications

A Novel Task Partitioning Method for Multi-core Processor Based-on Cohesion and Coupling

A Novel Task Partitioning Method for Multi-core Processor Based-on Cohesion and Coupling

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