ArticlePhysics in medicine and biology2017
Accelerated Monte Carlo simulation on the chemical stage in water radiolysis using GPU.
Article in Physics in medicine and biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Article
- Investigating radical yield variations in FLASH and conventional proton irradiation via microscopic Monte Carlo simulations.Physics in medicine and biology · 2025Article
- The Effects of Particle LET and Fluence on the Complexity and Frequency of Clustered DNA Damage.DNA · 2024Article
- TRAX-CHEMxt: Towards the Homogeneous Chemical Stage of Radiation Damage.International journal of molecular sciences · 2023Article
- A phenomenological model of proton FLASH oxygen depletion effects depending on tissue vasculature and oxygen supply.Frontiers in oncology · 2022Article
- Recent Developments on gMicroMC: Transport Simulations of Proton and Heavy Ions and Concurrent Transport of Radicals and DNA.International journal of molecular sciences · 2021Article
- Modeling the effect of oxygen on the chemical stage of water radiolysis using GPU-based microscopic Monte Carlo simulations, with an application in FLASH radiotherapy.Physics in medicine and biology · 2021Article
- MPEXS-DNA, a new GPU-based Monte Carlo simulator for track structures and radiation chemistry at subcellular scale.Medical physics · 2019Article
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Authors and funding
3 authors.
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Abstract
The accurate simulation of water radiolysis is an important step to understand the mechanisms of radiobiology and quantitatively test some hypotheses regarding radiobiological effects. However, the simulation of water radiolysis is highly time consuming, taking hours or even days to be completed by a conventional CPU processor. This time limitation hinders cell-level simulations for a number of research studies. We recently initiated efforts to develop gMicroMC, a GPU-based fast microscopic MC simulation package for water radiolysis. The first step of this project focused on accelerating the simulation of the chemical stage, the most time consuming stage in the entire water radiolysis process. A GPU-friendly parallelization strategy was designed to address the highly correlated many-body simulation problem caused by the mutual competitive chemical reactions between the radiolytic molecules. Two cases were tested, using a 750 keV electron and a 5 MeV proton incident in pure water, respectively. The time-dependent yields of all the radiolytic species during the chemical stage were used to evaluate the accuracy of the simulation. The relative differences between our simulation and the Geant4-DNA simulation were on average 5.3% and 4.4% for the two cases. Our package, executed on an Nvidia Titan black GPU card, successfully completed the chemical stage simulation of the two cases within 599.2 s and 489.0 s. As compared with Geant4-DNA that was executed on an Intel i7-5500U CPU processor and needed 28.6 h and 26.8 h for the two cases using a single CPU core, our package achieved a speed-up factor of 171.1-197.2.
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