Parallelization of a multi-blocked CFD code via three strategies for fluid flow and heat transfer analysis
(2004) In Computers & Fluids 33(1). p.57-80- Abstract
- This paper reports on a parallel implementation of a general 3D multi-block CFD code. The parallelization is achieved by using three strategies. Firstly, it is done on dual-processor PC-clusters where Windows NT systems are running. A multi-thread programming model is adopted for the multi-block code, where one thread corresponds to a block. Shared-memory is used for the exchange of inner-boundaries between neighboring blocks (threads) on the same node, while WinSockets are employed for those on different nodes. Secondly, the parallelization is extended to UNIX operating system. MPI is applied for all the message passing between different processors, including those on the same node. Thirdly, Pthreads (POSIX threads), a standardized... (More)
- This paper reports on a parallel implementation of a general 3D multi-block CFD code. The parallelization is achieved by using three strategies. Firstly, it is done on dual-processor PC-clusters where Windows NT systems are running. A multi-thread programming model is adopted for the multi-block code, where one thread corresponds to a block. Shared-memory is used for the exchange of inner-boundaries between neighboring blocks (threads) on the same node, while WinSockets are employed for those on different nodes. Secondly, the parallelization is extended to UNIX operating system. MPI is applied for all the message passing between different processors, including those on the same node. Thirdly, Pthreads (POSIX threads), a standardized application interface for threads, are adopted to take the advantage of the shared-memory feature of the SMP nodes, while MPI is only applied for the message passing between processors on different nodes. In all the strategies, a static load-balancing method is employed for equitable distribution of computational work to specified nodes. The parameters of the present code is studied in detail to facilitate the explanation of the speedup results. Two examples are provided to show the speedup and load balancing of the parallel calculation. Detailed comparison is made to evaluate the efficiency of different strategies. (C) 2003 Elsevier Ltd. All rights reserved. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/300593
- author
- Jia, Rongguang LU and Sundén, Bengt LU
- organization
- publishing date
- 2004
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- multi-block, multi-thread, heat transfer, cluster, parallel, MPI
- in
- Computers & Fluids
- volume
- 33
- issue
- 1
- pages
- 57 - 80
- publisher
- Elsevier
- external identifiers
-
- wos:000185555400004
- scopus:0041340564
- ISSN
- 0045-7930
- DOI
- 10.1016/S0045-7930(03)00029-X
- language
- English
- LU publication?
- yes
- id
- bbf1a2a3-1f33-41bf-a1f2-a2ff877dadae (old id 300593)
- date added to LUP
- 2016-04-01 16:28:22
- date last changed
- 2022-02-27 21:29:30
@article{bbf1a2a3-1f33-41bf-a1f2-a2ff877dadae,
abstract = {{This paper reports on a parallel implementation of a general 3D multi-block CFD code. The parallelization is achieved by using three strategies. Firstly, it is done on dual-processor PC-clusters where Windows NT systems are running. A multi-thread programming model is adopted for the multi-block code, where one thread corresponds to a block. Shared-memory is used for the exchange of inner-boundaries between neighboring blocks (threads) on the same node, while WinSockets are employed for those on different nodes. Secondly, the parallelization is extended to UNIX operating system. MPI is applied for all the message passing between different processors, including those on the same node. Thirdly, Pthreads (POSIX threads), a standardized application interface for threads, are adopted to take the advantage of the shared-memory feature of the SMP nodes, while MPI is only applied for the message passing between processors on different nodes. In all the strategies, a static load-balancing method is employed for equitable distribution of computational work to specified nodes. The parameters of the present code is studied in detail to facilitate the explanation of the speedup results. Two examples are provided to show the speedup and load balancing of the parallel calculation. Detailed comparison is made to evaluate the efficiency of different strategies. (C) 2003 Elsevier Ltd. All rights reserved.}},
author = {{Jia, Rongguang and Sundén, Bengt}},
issn = {{0045-7930}},
keywords = {{multi-block; multi-thread; heat transfer; cluster; parallel; MPI}},
language = {{eng}},
number = {{1}},
pages = {{57--80}},
publisher = {{Elsevier}},
series = {{Computers & Fluids}},
title = {{Parallelization of a multi-blocked CFD code via three strategies for fluid flow and heat transfer analysis}},
url = {{http://dx.doi.org/10.1016/S0045-7930(03)00029-X}},
doi = {{10.1016/S0045-7930(03)00029-X}},
volume = {{33}},
year = {{2004}},
}