Adaptive Memory Saving Strategy in Shielding Calculation of RMC

\nRMC(Reactor Monte Carlo) is a Monte Carlo simulation software used in reactor design and has been verified by different benchmarks. The former data structure and algorithm have been optimized for criticality and burn-up calculation making it inconvenient to be implemented into shielding simulation and variance reduction. In order to expand its availability in shielding calculation, several optimizations have been made in RMC code design to elevate efficiency in variance reduction. Considering parallel computation has been implemented in Monte Carlo simulation for long time, in this paper we proposed an adaptive memory saving strategy specifically designed for boosting parallel variance reduction calculation in RMC. We further found that this strategy can be very effective in certain condition without sacrificing any calculation performance.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-10-15
DOI
https://doi.org/10.1051/epjconf/202430204009/pdf
Primary Topic
Plant pathogens and resistance mechanisms
Type
article
Field-Weighted Citation Impact
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article

Adaptive Memory Saving Strategy in Shielding Calculation of RMC

Springer Link (Chiba Institute of Technology)
Plant pathogens and resistance mechanisms
article

Adaptive Memory Saving Strategy in Shielding Calculation of RMC

article en

Abstract

\nRMC(Reactor Monte Carlo) is a Monte Carlo simulation software used in reactor design and has been verified by different benchmarks. The former data structure and algorithm have been optimized for criticality and burn-up calculation making it inconvenient to be implemented into shielding simulation and variance reduction. In order to expand its availability in shielding calculation, several optimizations have been made in RMC code design to elevate efficiency in variance reduction. Considering parallel computation has been implemented in Monte Carlo simulation for long time, in this paper we proposed an adaptive memory saving strategy specifically designed for boosting parallel variance reduction calculation in RMC. We further found that this strategy can be very effective in certain condition without sacrificing any calculation performance.\n

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 40%
Plant pathogens and resistance mechanisms
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