Vascular System Modeling in Parallel Environment - Distributed and Shared Memory Approaches

This paper presents two approaches in parallel modeling of vascular system development in internal organs. In the first approach, new parts of tissue are distributed among processors and each processor is responsible for perfusing its assigned parts of tissue to all vascular trees. Communication bet...

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Bibliographic Details
Published in:IEEE transactions on information technology in biomedicine Vol. 15; no. 4; pp. 668 - 672
Main Authors: Jurczuk, K., Kretowski, M., Bezy-Wendling, J.
Format: Journal Article
Language:English
Published: United States IEEE 01.07.2011
Institute of Electrical and Electronics Engineers
Subjects:
Adult
Algorithm design and analysis
Algorithms
Bifurcation
Bioengineering
Blood
Cardiovascular Physiological Phenomena
Computational Biology
Computational Biology - methods
Computational modeling
Computer Science
Computer Simulation
distributed memory algorithms
Distributed, Parallel, and Cluster Computing
Engineering Sciences
Hepatic Artery
Hepatic Artery - anatomy & histology
Hepatic Veins
Hepatic Veins - anatomy & histology
Humans
Life Sciences
Liver
Liver - anatomy & histology
Liver - blood supply
Models, Cardiovascular
parallel computing
Program processors
Shape
shared memory algorithms
Signal and Image processing
vascular system
Veins
vascular system
shared memory algorithms
distributed memory algorithms
computational modeling
parallel computing
ISSN:1089-7771, 1558-0032, 1558-0032
Online Access:Get full text
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Summary:This paper presents two approaches in parallel modeling of vascular system development in internal organs. In the first approach, new parts of tissue are distributed among processors and each processor is responsible for perfusing its assigned parts of tissue to all vascular trees. Communication between processors is accomplished by passing messages, and therefore, this algorithm is perfectly suited for distributed memory architectures. The second approach is designed for shared memory machines. It parallelizes the perfusion process during which individual processing units perform calculations concerning different vascular trees. The experimental results, performed on a computing cluster and multicore machines, show that both algorithms provide a significant speedup.
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ISSN:1089-7771
1558-0032
1558-0032
DOI:10.1109/TITB.2011.2151198