Mapping task graphs onto Network Processors using genetic algorithm

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This book presents an automated task scheduling
technique to address this parallel programming
complexity. Our proposed technique is based on GA. By
incorporating tasks dependency into scheduling list
and encoding task scheduling list as a chromosome, GA
can quickly remove the invalid mappings and evolve to
the high quality solutions. This technique takes
advantage of task-level and application-level
parallelism to maximize system performance for a
given NPs architecture. The simulation results show
that this proposed technique can generate high
quality mapping comparing to other heuristics by
mapping some sample network applications. This work
will also enable researchers and engineers to
systematically evaluate and quantitatively understand
the NPs system issues including application
partitioning, architecture organizing, workload
mapping and run-time operating

Autorentext

Nandeesh KumarDepartment of Electrical and Computer EngineeringThe Graduate SchoolSouthern Illinois University CarbondalePublication:Mapping Task Graphs onto Network Processors Using GeneticAlgorithm. Accepted and to be appear in Proc. of 6th ACS/IEEEInternational Conference on Computer Systems and Applications(AICCSA-08), March 2008


Klappentext

This book presents an automated task schedulingtechnique to address this parallel programmingcomplexity. Our proposed technique is based on GA. Byincorporating tasks dependency into scheduling listand encoding task scheduling list as a chromosome, GAcan quickly remove the invalid mappings and evolve tothe high quality solutions. This technique takesadvantage of task-level and application-levelparallelism to maximize system performance for agiven NPs architecture. The simulation results showthat this proposed technique can generate highquality mapping comparing to other heuristics bymapping some sample network applications. This workwill also enable researchers and engineers tosystematically evaluate and quantitatively understandthe NPs system issues including applicationpartitioning, architecture organizing, workloadmapping and run-time operating

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783639136692
    • Sprache Englisch
    • Größe H220mm x B4mm x T150mm
    • Jahr 2013
    • EAN 9783639136692
    • Format Kartonierter Einband
    • ISBN 978-3-639-13669-2
    • Titel Mapping task graphs onto Network Processors using genetic algorithm
    • Autor Nandeesh Kumar
    • Untertitel Multi-Task Processing
    • Gewicht 92g
    • Herausgeber VDM Verlag Dr. Müller e.K.
    • Anzahl Seiten 56
    • Genre Informatik

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