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International Parallel and Distributed Processing Symposium (IPDPS'03)
Lazy Parallelization: A Finite State Machine Based Optimization Approach for Data Parallel Image Processing Applications
Nice, France
April 22-April 26
ISBN: 0-7695-1926-1
ASCII Text
x 
 
F.J. Seinstra, D. Koelma, "Lazy Parallelization: A Finite State Machine Based Optimization Approach for Data Parallel Image Processing Applications," Parallel and Distributed Processing Symposium, International, pp. 229b, International Parallel and Distributed Processing Symposium (IPDPS'03), 2003.
 
 
BibTex
x
 
@article{ 10.1109/IPDPS.2003.1213418,
author = {F.J. Seinstra and D. Koelma},
title = {Lazy Parallelization: A Finite State Machine Based Optimization Approach for Data Parallel Image Processing Applications},
journal ={Parallel and Distributed Processing Symposium, International},
volume = {0},
year = {2003},
issn = {1530-2075},
pages = {229b},
doi = {http://doi.ieeecomputersociety.org/10.1109/IPDPS.2003.1213418},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Parallel and Distributed Processing Symposium, International
TI - Lazy Parallelization: A Finite State Machine Based Optimization Approach for Data Parallel Image Processing Applications
SN - 1530-2075
SP
EP
A1 - F.J. Seinstra,
A1 - D. Koelma,
PY - 2003
KW - null
VL - 0
JA - Parallel and Distributed Processing Symposium, International
ER -
 
F.J. Seinstra, University of Amsterdam
D. Koelma, University of Amsterdam
Performance obtained with existing library-based parallelization tools for implementing high performance image processing applications is often sub-optimal. This is because inter-operation optimization (or: optimization across library calls) is often not incorporated in the library implementations. This paper presents a simple, efficient, finite state machine-based method for global performance optimization, called ?lazy parallelization?. Experimental results based on this approach show significant performance improvements over non-optimized parallel implementations.
Citation:
F.J. Seinstra, D. Koelma, "Lazy Parallelization: A Finite State Machine Based Optimization Approach for Data Parallel Image Processing Applications," ipdps, pp.229b, International Parallel and Distributed Processing Symposium (IPDPS'03), 2003
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