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Division Spotlight
Nuclear Installations Safety
Devoted specifically to the safety of nuclear installations and the health and safety of the public, this division seeks a better understanding of the role of safety in the design, construction and operation of nuclear installation facilities. The division also promotes engineering and scientific technology advancement associated with the safety of such facilities.
Meeting Spotlight
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
Digital control system installed at China’s Linglong One
Earlier this month, the first digital control system was put in place at Linglong One, a small modular reactor demonstration project being built at the Changjiang nuclear power plant in Hainan Province. This is the world’s first land-based commercial SMR and is controlled by China National Nuclear Power Co. Ltd., a subsidiary of the China National Nuclear Corporation (CNNC).
Tianyu Liu, Noah Wolfe, Christopher D. Carothers, Wei Ji, X. George Xu
Nuclear Science and Engineering | Volume 185 | Number 1 | January 2017 | Pages 232-242
Technical Note | doi.org/10.13182/NSE16-33
Articles are hosted by Taylor and Francis Online.
XSBench is a proxy application used to study the performance of nuclear macroscopic cross-section data construction, which is usually the most time-consuming process in Monte Carlo neutron transport simulations. In this technical note we report on our experience in optimizing XSBench to Intel multicore central processing units (CPUs), many integrated core coprocessors (MICs), and Nvidia graphics processing units (GPUs). The continuous-energy cross-section construction in the Monte Carlo simulation of the Hoogenboom-Martin large problem is used in our benchmark. We demonstrate that through several tuning techniques, particularly data prefetch, the performance of XSBench on each platform can be desirably improved compared to the original implementation on the same platform. It is shown that the performance gain is 1.46× on the Westmere CPU, 1.51× on the Haswell CPU, 2.25× on the Knights Corner (KNC) MIC, and 5.98× on the Kepler GPU. The comparison across different platforms shows that when using the high-end Haswell CPU as the baseline, the KNC MIC is 1.63× faster while the high-end Kepler GPU is 2.20× faster.