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This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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Strontium: Supply-and-demand success for the DOE’s Isotope Program
The Department of Energy’s Isotope Program (DOE IP) announced last week that it would end its “active standby” capability for strontium-82 production about two decades after beginning production of the isotope for cardiac diagnostic imaging. The DOE IP is celebrating commercialization of the Sr-82 supply chain as “a success story for both industry and the DOE IP.” Now that the Sr-82 market is commercially viable, the DOE IP and its National Isotope Development Center can “reassign those dedicated radioisotope production capacities to other mission needs”—including Sr-89.
Kenji Higuchi, Kiyoshi Asai, Yukihiro Hasegawa
Nuclear Science and Engineering | Volume 127 | Number 1 | September 1997 | Pages 78-88
Technical Paper | doi.org/10.13182/NSE97-A1922
Articles are hosted by Taylor and Francis Online.
Experiences with vectorization of production-level Monte Carlo codes such as KENO-IV, MCNP, VIM, and MORSE have shown that it is difficult to attain high speedup ratios on vector processors because of indirect addressing, nests of conditional branches, short vector length, cache misses, and operations for realization of robustness and generality. A previous work has already shown that the first, second, and third difficulties can be resolved by using special computer hardware for vector processing of Monte Carlo codes. Here, the fourth and fifth difficulties are discussed in detail using the results for a vectorized version of the MORSE code. As for the fourth difficulty, it is shown that the cache miss-hit ratio affects execution times of the vectorized Monte Carlo codes and the ratio strongly depends on the number of the particles simultaneously tracked. As for the fifth difficulty, it is shown that remarkable speedup ratios are obtained by removing operations that are not essential to the specific problem being solved. These experiences have shown that if a production-level Monte Carlo code system had a capability to selectively construct source coding that complements the input data, then the resulting code could achieve much higher performance.