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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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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ANS joins others in seeking to discuss SNF/HLW impasse
The American Nuclear Society joined seven other organizations to send a letter to Energy Secretary Christopher Wright on July 8, asking to meet with him to discuss “the restoration of a highly functioning program to meet DOE’s legal responsibility to manage and dispose of the nation’s commercial and legacy defense spent nuclear fuel (SNF) and high-level radioactive waste (HLW).”
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.