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Performance Evaluation of Convolution on the Cell Broadband Engine Processor
February 2011 (vol. 22 no. 2)
pp. 337-351
ASCII Text
x 
 
Leila Ismail, Driss Guerchi, "Performance Evaluation of Convolution on the Cell Broadband Engine Processor," IEEE Transactions on Parallel and Distributed Systems, vol. 22, no. 2, pp. 337-351, February, 2011.
 
 
BibTex
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@article{ 10.1109/TPDS.2010.70,
author = {Leila Ismail and Driss Guerchi},
title = {Performance Evaluation of Convolution on the Cell Broadband Engine Processor},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {22},
number = {2},
issn = {1045-9219},
year = {2011},
pages = {337-351},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2010.70},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - Performance Evaluation of Convolution on the Cell Broadband Engine Processor
IS - 2
SN - 1045-9219
SP337
EP351
EPD - 337-351
A1 - Leila Ismail,
A1 - Driss Guerchi,
PY - 2011
KW - Parallel computing
KW - IBM Cell BE
KW - convolution
KW - performance.
VL - 22
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 
Leila Ismail, UAE University, Al-Ain
Driss Guerchi, UAE University, Al-Ain
Convolution represents a major computational load for many scientific and engineering applications, including seismic surface simulations and seismic imaging. Since convolution presents a heavy computational load, increasing its efficiency can significantly enhance the performance of associated applications. In this work, we present an in-depth analysis of the convolution algorithm and its complexity in order to develop adequate parallel algorithms. The implementation of these algorithms and their evaluation on the IBM Cell Broadband Engine (BE) processor reveals the gains and losses achieved by parallelizing the direct convolution. The performance results show that despite the complexity of the convolution processing, a speedup gain of at least 71.4 is obtained. The parallel vectorized algorithm requires the development effort of considering three independent vectorization strategies. Given the wide availability of Cell processors, the proposed parallelization approach can be widely adopted by any convolution-based application.

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Index Terms:
Parallel computing, IBM Cell BE, convolution, performance.
Citation:
Leila Ismail, Driss Guerchi, "Performance Evaluation of Convolution on the Cell Broadband Engine Processor," IEEE Transactions on Parallel and Distributed Systems, vol. 22, no. 2, pp. 337-351, Feb. 2011, doi:10.1109/TPDS.2010.70
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