Theoretical and experimental study on large size image processing applications using divisible load paradigm on distributed bus networks-Reference-Cited by-同舟云学术

Theoretical and experimental study on large size image processing applications using divisible load paradigm on distributed bus networks

Published:2002-12 Issue:13-14 Volume:20 Page:917-935
ISSN:0262-8856
Container-title:Image and Vision Computing
language:en
Short-container-title:Image and Vision Computing

Author:

Veeravalli Bharadwaj,Ranganath Surendra

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing

Reference24 articles.

1. Load partitioning and trade-off study for large matrixmatrix–vectorvector computations in multicast bus networks with communication delays;Ghose;Journal of Parallel and Distributed Computing,1998

2. Scheduling Divisible Loads in Parallel and Distributed Systems;Bharadwaj,1996

3. Efficient partitioning and scheduling of computer vision and image processing data on bus networks using divisible load analysis;Bharadwaj;Image and Vision Computing,2000

4. Distributed computation with communication delays;Cheng;IEEE Transactions on Aerospace and Electronic Systems,1988

5. M. Drozdowski, Selected problems of scheduling tasks in multiprocessor computer systems, Wydawnictwa Politechniki Poznanskiej (in English), Book No. 321, Poznan, Poland, 1997.

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