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Autori principali: Butson, Simon, Cleveland, Mathew, Long, Alex, Palmer, Todd
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2506.11962
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author Butson, Simon
Cleveland, Mathew
Long, Alex
Palmer, Todd
author_facet Butson, Simon
Cleveland, Mathew
Long, Alex
Palmer, Todd
contents This work describes methodologies to successfully implement the Implicit Monte Carlo (IMC) scheme for thermal radiative transfer in reduced-precision floating-point arithmetic. The methods used can be broadly categorized into scaling approaches and floating-point arithmetic manipulations. Scaling approaches entail re-scaling values to ensure computations stay within a representable range. Floating-point arithmetic manipulations involve changes to order of operations and alternative summation algorithms to minimize errors in calculations. The Implicit Monte Carlo method has nonlinear dependencies, quantities spanning many orders of magnitude, and a sensitive coupling between radiation and material energy that provide significant difficulties to accurate reduced-precision implementations. Results from reduced and higher-precision implementations of IMC solving the Su & Olson volume source benchmark problem are compared to demonstrate the accuracy of a correctly implemented reduced-precision IMC code. We show that the scaling approaches and floating-point manipulations used in this work can produce solutions with similar accuracy using half-precision data types as compared to a standard double-precision implementation.
format Preprint
id arxiv_https___arxiv_org_abs_2506_11962
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Accurate Reduced Floating-Point Precision Implicit Monte Carlo
Butson, Simon
Cleveland, Mathew
Long, Alex
Palmer, Todd
Computational Physics
This work describes methodologies to successfully implement the Implicit Monte Carlo (IMC) scheme for thermal radiative transfer in reduced-precision floating-point arithmetic. The methods used can be broadly categorized into scaling approaches and floating-point arithmetic manipulations. Scaling approaches entail re-scaling values to ensure computations stay within a representable range. Floating-point arithmetic manipulations involve changes to order of operations and alternative summation algorithms to minimize errors in calculations. The Implicit Monte Carlo method has nonlinear dependencies, quantities spanning many orders of magnitude, and a sensitive coupling between radiation and material energy that provide significant difficulties to accurate reduced-precision implementations. Results from reduced and higher-precision implementations of IMC solving the Su & Olson volume source benchmark problem are compared to demonstrate the accuracy of a correctly implemented reduced-precision IMC code. We show that the scaling approaches and floating-point manipulations used in this work can produce solutions with similar accuracy using half-precision data types as compared to a standard double-precision implementation.
title Accurate Reduced Floating-Point Precision Implicit Monte Carlo
topic Computational Physics
url https://arxiv.org/abs/2506.11962