DALB-MC: dynamic Adaptive load balancing for efficient Monte Carlo particle transport on heterogeneous architectures
This paper proposes a Dynamic Adaptive Load Balancing Algorithm for Monte Carlo Particle Transport (DALB-MC algorithm) to enhance computational performance of Monte Carlo codes, particularly in heterogeneous environments. While Monte Carlo codes have adopted local thread parallelism and global paral...
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| Published in: | Journal of nuclear science and technology Vol. 62; no. 11; pp. 1100 - 1111 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
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Tokyo
Taylor & Francis
02.11.2025
Taylor & Francis Ltd |
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| ISSN: | 0022-3131, 1881-1248 |
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| Abstract | This paper proposes a Dynamic Adaptive Load Balancing Algorithm for Monte Carlo Particle Transport (DALB-MC algorithm) to enhance computational performance of Monte Carlo codes, particularly in heterogeneous environments. While Monte Carlo codes have adopted local thread parallelism and global parallelism through message passing between nodes, traditional parallel algorithms face challenges in adapting to diverse hardware resources like tailing effect and long particle history in weight-window method. The proposed DALB-MC algorithm addresses this by dynamically partitioning tasks into sub-tasks and allocating them in real time based on each node's computational capacity, ensuring optimized resource utilization and reduced simulation time. Implemented on MCShield, the algorithm achieves approximately 20% computation time reduction in massively parallel simulations and significantly improves overall efficiency. To verify its effectiveness, self-defined arithmetic examples confirm the correctness of the algorithm, and additional tests on a Linux supercomputing platform with a complex benchmark case demonstrate its scalability and performance optimization under real-world engineering applications. The results highlight DALB-MC algorithm's capability to adaptively balance workloads, making it highly suitable for modern Monte Carlo particle transport simulations in diverse computational environments. |
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| AbstractList | This paper proposes a Dynamic Adaptive Load Balancing Algorithm for Monte Carlo Particle Transport (DALB-MC algorithm) to enhance computational performance of Monte Carlo codes, particularly in heterogeneous environments. While Monte Carlo codes have adopted local thread parallelism and global parallelism through message passing between nodes, traditional parallel algorithms face challenges in adapting to diverse hardware resources like tailing effect and long particle history in weight-window method. The proposed DALB-MC algorithm addresses this by dynamically partitioning tasks into sub-tasks and allocating them in real time based on each node’s computational capacity, ensuring optimized resource utilization and reduced simulation time. Implemented on MCShield, the algorithm achieves approximately 20% computation time reduction in massively parallel simulations and significantly improves overall efficiency. To verify its effectiveness, self-defined arithmetic examples confirm the correctness of the algorithm, and additional tests on a Linux supercomputing platform with a complex benchmark case demonstrate its scalability and performance optimization under real-world engineering applications. The results highlight DALB-MC algorithm’s capability to adaptively balance workloads, making it highly suitable for modern Monte Carlo particle transport simulations in diverse computational environments. |
| Author | Wu, Jiajun Zhang, Hui Pu, Yanheng Qiu, Rui Wu, Zhen Hu, Ankang Li, Junli |
| Author_xml | – sequence: 1 givenname: Jiajun surname: Wu fullname: Wu, Jiajun organization: Key Laboratory of Particle and Radiation Imaging of Ministry of Education – sequence: 2 givenname: Hui surname: Zhang fullname: Zhang, Hui organization: Key Laboratory of Particle and Radiation Imaging of Ministry of Education – sequence: 3 givenname: Ankang surname: Hu fullname: Hu, Ankang organization: Key Laboratory of Particle and Radiation Imaging of Ministry of Education – sequence: 4 givenname: Yanheng surname: Pu fullname: Pu, Yanheng organization: Key Laboratory of Particle and Radiation Imaging of Ministry of Education – sequence: 5 givenname: Zhen surname: Wu fullname: Wu, Zhen email: wuzhen97@tsinghua.org.cn organization: Nuctech Company Limited – sequence: 6 givenname: Rui surname: Qiu fullname: Qiu, Rui organization: Key Laboratory of Particle and Radiation Imaging of Ministry of Education – sequence: 7 givenname: Junli surname: Li fullname: Li, Junli organization: Key Laboratory of Particle and Radiation Imaging of Ministry of Education |
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| Cites_doi | 10.15669/pnst.2.1 10.1016/j.cpc.2016.05.019 10.1145/1048935.1050176 10.1016/j.nds.2014.07.049 10.1016/S0168-9002(03)01368-8 10.17485/ijst/2017/v10i25/105688 10.1007/11752578 10.4018/978-1-7998-1021-6.ch016 10.5281/zenodo.12599358 10.2172/877459 10.1016/j.anucene.2014.07.048 10.1007/978-3-642-55224-3_5 10.5296/npa.v4i1.1290 |
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| Copyright | 2025 Atomic Energy Society of Japan. All rights reserved. 2025 2025 Atomic Energy Society of Japan. All rights reserved. |
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| SubjectTerms | Adaptive algorithms Algorithms Computer simulation Load balancing load balancing algorithm Mcshield Message passing Monte Carlo simulation multicore processors parallel computing efficiency Parallel processing Resource utilization |
| Title | DALB-MC: dynamic Adaptive load balancing for efficient Monte Carlo particle transport on heterogeneous architectures |
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