Adaptive genetic algorithm for energy-efficient task scheduling on asymmetric multiprocessor system-on-chip-Reference-Cited by-同舟云学术

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Adaptive genetic algorithm for energy-efficient task scheduling on asymmetric multiprocessor system-on-chip

Published:2019-04 Issue: Volume:66 Page:19-30
ISSN:0141-9331
Container-title:Microprocessors and Microsystems
language:en
Short-container-title:Microprocessors and Microsystems

Author:

Yun Yonghee,Hwang Eun Ju,Kim Young Hwan

Funder

IITP

Institute for Information & Communications Technology Promotion

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Software

Reference28 articles.

1. Scenario-based run-time adaptive Multi-Processor System-on-Chip;Quan,2015

2. Multiprocessor system on-chip (MPSoC) technology;Wolf;IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.,2008

3. Static scheduling algorithms for allocating directed task graphs to multiprocessors;Kwok;ACM Comput. Surv.,1999

4. A Comparison of eleven static heuristics for scheduling a class of independent tasks onto heterogeneous distributed computing systems;Braun;J. Parallel Distrib. Comput.,2001

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4. JHTD: An Efficient Joint Scheduling Framework Based on Hypergraph for Task Placement and Data Transfer Across Geographically Distributed Data Centers;IEEE Access;2022

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