In recent years,graphics processing units(GPUs)have been applied to accelerate Monte Carlo(MC)simulations for proton dose calculation in radiotherapy.Nonetheless,current GPU platforms,such as Compute Unified Device Ar...In recent years,graphics processing units(GPUs)have been applied to accelerate Monte Carlo(MC)simulations for proton dose calculation in radiotherapy.Nonetheless,current GPU platforms,such as Compute Unified Device Architecture(CUDA)and Open Computing Language(OpenCL),suffer from cross-platform limitation or relatively high programming barrier.However,the Taichi toolkit,which was developed to overcome these difficulties,has been successfully applied to high-performance numerical computations.Based on the class II condensed history simulation scheme with various proton-nucleus interactions,we developed a GPU-accelerated MC engine for proton transport using the Taichi toolkit.Dose distributions in homogeneous and heterogeneous geometries were calculated for 110,160,and 200 MeV protons and were compared with those obtained by full MC simulations using TOPAS.The gamma passing rates were greater than 0.99 and 0.95 with criteria of 2 mm,2%and 1 mm,1%,respectively,in all the benchmark tests.Moreover,the calculation speed was at least 5800 times faster than that of TOPAS,and the number of lines of code was approximately 10 times less than those of CUDA or OpenCL.Our study provides a highly accurate,efficient,and easy-to-use proton dose calculation engine for fast prototyping,beamlet calculation,and education purposes.展开更多
基金supported by the National Natural Science Foundation of China (Nos.11735003,11975041,and 11961141004)。
文摘In recent years,graphics processing units(GPUs)have been applied to accelerate Monte Carlo(MC)simulations for proton dose calculation in radiotherapy.Nonetheless,current GPU platforms,such as Compute Unified Device Architecture(CUDA)and Open Computing Language(OpenCL),suffer from cross-platform limitation or relatively high programming barrier.However,the Taichi toolkit,which was developed to overcome these difficulties,has been successfully applied to high-performance numerical computations.Based on the class II condensed history simulation scheme with various proton-nucleus interactions,we developed a GPU-accelerated MC engine for proton transport using the Taichi toolkit.Dose distributions in homogeneous and heterogeneous geometries were calculated for 110,160,and 200 MeV protons and were compared with those obtained by full MC simulations using TOPAS.The gamma passing rates were greater than 0.99 and 0.95 with criteria of 2 mm,2%and 1 mm,1%,respectively,in all the benchmark tests.Moreover,the calculation speed was at least 5800 times faster than that of TOPAS,and the number of lines of code was approximately 10 times less than those of CUDA or OpenCL.Our study provides a highly accurate,efficient,and easy-to-use proton dose calculation engine for fast prototyping,beamlet calculation,and education purposes.
