ANT-MOC: Scalable Neutral Particle Transport Using 3D Method of Characteristics on Multi-GPU Systems
The Method Of Characteristic (MOC) to solve the Neutron Transport Equation (NTE) is the core of full-core simulation for reactors. High resolution is enabled by discretizing the NTE through massive tracks to traverse the 3D reactor geometry. However, the 3D full-core simulation is prohibitively expe...
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| Vydáno v: | International Conference for High Performance Computing, Networking, Storage and Analysis (Online) s. 1 - 13 |
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| Jazyk: | angličtina |
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ACM
11.11.2023
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| ISSN: | 2167-4337 |
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| Abstract | The Method Of Characteristic (MOC) to solve the Neutron Transport Equation (NTE) is the core of full-core simulation for reactors. High resolution is enabled by discretizing the NTE through massive tracks to traverse the 3D reactor geometry. However, the 3D full-core simulation is prohibitively expensive because of the high memory consumption and the severe load imbalance. To deal with these challenges, we develop ANT-MOC 1 1 The name "ANT-MOC" is inspired by the cooperative transport behavior of ants, which allows them to efficiently exploit resources from their environment.. Specifically, we build a performance model for memory footprint, computation and communication, based on which a track management strategy is proposed to overcome the resolution bottlenecks caused by limited GPU memory. Furthermore, we implement a novel multi-level load mapping strategy to ensure load balancing among nodes, GPUs, and CUs. ANT-MOC enables a 3D full-core reactor simulation with 100 billion tracks on 16,000 GPUs, with 70.69% and 89.38% parallel efficiency for strong scalability and weak scalability, respectively. |
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| AbstractList | The Method Of Characteristic (MOC) to solve the Neutron Transport Equation (NTE) is the core of full-core simulation for reactors. High resolution is enabled by discretizing the NTE through massive tracks to traverse the 3D reactor geometry. However, the 3D full-core simulation is prohibitively expensive because of the high memory consumption and the severe load imbalance. To deal with these challenges, we develop ANT-MOC 1 1 The name "ANT-MOC" is inspired by the cooperative transport behavior of ants, which allows them to efficiently exploit resources from their environment.. Specifically, we build a performance model for memory footprint, computation and communication, based on which a track management strategy is proposed to overcome the resolution bottlenecks caused by limited GPU memory. Furthermore, we implement a novel multi-level load mapping strategy to ensure load balancing among nodes, GPUs, and CUs. ANT-MOC enables a 3D full-core reactor simulation with 100 billion tracks on 16,000 GPUs, with 70.69% and 89.38% parallel efficiency for strong scalability and weak scalability, respectively. |
| Author | Shi, Peng Chi, Xuebin Hu, Yun Bu, Lingkun Wang, Jue Xin, Zhikuang Li, Shigang Wang, Zongguo Feng, Yangde Li, Shunde Wang, Yangang |
| Author_xml | – sequence: 1 givenname: Shunde surname: Li fullname: Li, Shunde email: lishunde@cnic.cn organization: University of Chinese Academy of Sciences,Computer Network Information Center, Chinese Academy of Sciences,Beijing,China – sequence: 2 givenname: Zongguo surname: Wang fullname: Wang, Zongguo email: wangzg@cnic.cn organization: University of Chinese Academy of Sciences,Computer Network Information Center, Chinese Academy of Sciences,Beijing,China – sequence: 3 givenname: Lingkun surname: Bu fullname: Bu, Lingkun email: blk1997@126.com organization: University of Science and Technology Beijing,National Center for Materials Service Safety,Beijing,China – sequence: 4 givenname: Jue surname: Wang fullname: Wang, Jue email: wangjue@sccas.cn organization: University of Chinese Academy of Sciences,Computer Network Information Center, Chinese Academy of Sciences,Beijing,China – sequence: 5 givenname: Zhikuang surname: Xin fullname: Xin, Zhikuang email: xinzhikuang@cnic.cn organization: University of Chinese Academy of Sciences,Computer Network Information Center, Chinese Academy of Sciences,Beijing,China – sequence: 6 givenname: Shigang surname: Li fullname: Li, Shigang email: shigangli.cs@gmail.com organization: University of Science and Technology Beijing,National Center for Materials Service Safety,Beijing,China – sequence: 7 givenname: Yangang surname: Wang fullname: Wang, Yangang email: wangyg@cnic.cn organization: University of Chinese Academy of Sciences,Computer Network Information Center, Chinese Academy of Sciences,Beijing,China – sequence: 8 givenname: Yangde surname: Feng fullname: Feng, Yangde email: ydfeng@sccas.cn organization: University of Chinese Academy of Sciences,Computer Network Information Center, Chinese Academy of Sciences,Beijing,China – sequence: 9 givenname: Peng surname: Shi fullname: Shi, Peng email: pshi@ustb.edu.cn organization: University of Science and Technology Beijing,National Center for Materials Service Safety,Beijing,China – sequence: 10 givenname: Yun surname: Hu fullname: Hu, Yun email: evanhy@163.com organization: China Institute of Atomic Energy,Beijing,China – sequence: 11 givenname: Xuebin surname: Chi fullname: Chi, Xuebin email: chi@cnic.cn organization: University of Chinese Academy of Sciences,Computer Network Information Center, Chinese Academy of Sciences,Beijing,China |
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| Snippet | The Method Of Characteristic (MOC) to solve the Neutron Transport Equation (NTE) is the core of full-core simulation for reactors. High resolution is enabled... |
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| SubjectTerms | 3D method of characteristic Applied computing → Physics Computing methodologies → Massively parallel algorithms Graphics processing units Load balancing Memory management Multi-GPUs Neutron particle transport Neutrons Scalability Software Software algorithms Three-dimensional displays |
| Title | ANT-MOC: Scalable Neutral Particle Transport Using 3D Method of Characteristics on Multi-GPU Systems |
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