DocumentCode
2641320
Title
AMTHA: An Algorithm for Automatically Mapping Tasks to Processors in Heterogeneous Multiprocessor Architectures
Author
De Giusti, Laura ; Luque, Emilio ; Chichizola, Franco ; Naiouf, Marcelo ; De Giusti, Armando
Author_Institution
Sch. of Comput. Sci., UNLP, La Plata, Argentina
Volume
2
fYear
2009
fDate
March 31 2009-April 2 2009
Firstpage
481
Lastpage
485
Abstract
An automatic task-to-processor mapping algorithm is analyzed in parallel systems that run over loosely coupled distributed architectures. The MPAHA (Model on Parallel Algorithms on Heterogeneous Architectures) model that allows predicting parallel application performance running over heterogeneous architectures is presented. In particular, the heterogeneity of both processors and communications is taken into consideration. From the results obtained with the MPAHA model, the AMTHA (Automatic Mapping Task on Heterogeneous Architectures) algorithm for task-to-processors assignment is presented and its implementation is analyzed. Experimental results compare execution time obtained with AMTHA mapping scheme with those obtained using the known mapping algorithm HEFT (Heterogeneous - Earliest Finish - Time), using a simple heterogeneous multicluster architecture. Finally actual lines of research are presented, focusing extensions to multicore processors and Grid environments.
Keywords
multiprocessing systems; parallel algorithms; parallel architectures; AMTHA algorithm; Automatic Mapping Task on Heterogeneous Architecture; Grid environment; HEFT mapping algorithm; Heterogeneous-Earliest Finish-Time; MPAHA model; Model on Parallel Algorithms on Heterogeneous Architectures model; automatic task-to-processor mapping algorithm; distributed architecture; execution time; heterogeneous multicluster architecture; heterogeneous multiprocessor architecture; multicore processor; parallel application performance; parallel system; Algorithm design and analysis; Application software; Computer architecture; Computer science; Costs; Multicore processing; Operating systems; Parallel algorithms; Predictive models; Programming profession;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location
Los Angeles, CA
Print_ISBN
978-0-7695-3507-4
Type
conf
DOI
10.1109/CSIE.2009.175
Filename
5171385
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