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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Vydané v:	IEEE transactions on information technology in biomedicine Ročník 15; číslo 4; s. 668 - 672
Hlavní autori:	Jurczuk, K., Kretowski, M., Bezy-Wendling, J.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.07.2011 Institute of Electrical and Electronics Engineers
Predmet:	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
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Abstract	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.
AbstractList	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. 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.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. The 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 multi-core machines, show that both algorithms provide a significant speedup.
Author	Jurczuk, K. Bezy-Wendling, J. Kretowski, M.
AuthorAffiliation	2 LTSI, Laboratoire Traitement du Signal et de l'Image INSERM : U642 Université de Rennes 1 Campus de Beaulieu, 263 Avenue du Général Leclerc - CS 74205 - 35042 Rennes Cedex, FR 1 Faculty of Computer Science Bialystok Technical University - University of Bialystok Wiejska 45a, 15-351, Bialystok, PL
AuthorAffiliation_xml	– name: 1 Faculty of Computer Science Bialystok Technical University - University of Bialystok Wiejska 45a, 15-351, Bialystok, PL – name: 2 LTSI, Laboratoire Traitement du Signal et de l'Image INSERM : U642 Université de Rennes 1 Campus de Beaulieu, 263 Avenue du Général Leclerc - CS 74205 - 35042 Rennes Cedex, FR
Author_xml	– sequence: 1 givenname: K. surname: Jurczuk fullname: Jurczuk, K. email: k.jurczuk@pb.edu.pl organization: Fac. of Comput. Sci., Bialystok Univ. of Technol., Bialystok, Poland – sequence: 2 givenname: M. surname: Kretowski fullname: Kretowski, M. email: m.kretowski@pb.edu.pl organization: Fac. of Comput. Sci., Bialystok Univ. of Technol., Bialystok, Poland – sequence: 3 givenname: J. surname: Bezy-Wendling fullname: Bezy-Wendling, J. email: johanne.bezy@univ-rennes1.fr organization: INSERM, Rennes, France
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SubjectTerms	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
Title	Vascular System Modeling in Parallel Environment - Distributed and Shared Memory Approaches
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