ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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!
Latest Magazine Issues
Sep 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
October 2025
Nuclear Technology
September 2025
Fusion Science and Technology
Latest News
High temperature fission chambers engineered for AMR/SMR safety and performance
As the global energy landscape shifts towards safer, smaller, and more flexible nuclear power, Small Modular Reactors (SMRs) and Gen. IV* technologies are at the forefront of innovation. These advanced designs pose new challenges in size, efficiency, and operating environment that traditional instrumentation and control solutions aren’t always designed to handle.
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.