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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Vydané v:Journal of nuclear science and technology Ročník 62; číslo 11; s. 1100 - 1111
Hlavní autori: Wu, Jiajun, Zhang, Hui, Hu, Ankang, Pu, Yanheng, Wu, Zhen, Qiu, Rui, Li, Junli
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Tokyo Taylor & Francis 02.11.2025
Taylor & Francis Ltd
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ISSN:0022-3131, 1881-1248
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0022-3131
1881-1248
DOI:10.1080/00223131.2025.2526784