基于CUDA的大型γ辐照装置通用并行排源算法

General-Purpose Parallel Algorithm Based on CUDA for Source Pencils' Deployment of Large γ Irradiator

本文利用CUDA执行模型实现了植物模拟生长算法的完全并行化,结合标准排源质量评价数学模型,得到了一种高效率的并行排源算法,对应的代码能运行在GPU上。在此基础上,利用若干不同规模的排源算例对新版本算法进行了测试。测试结果表明,在保持已有版本算法优点的基础上,新算法的计算效率相对CPU版本提升了500倍以上,相对CPU+GPU混合版本,也提升了30倍以上。对111PBq以下装置,新算法的计算时间小于10min。利用单GTX275GPU,新算法的计算性能上限为167PBq左右,时间不超过25min,利用多GPU还可提高计算能力。综上所述,基于GPU的新版本算法可满足目前国内任意规模γ辐照装置的高质量排源需要,具有高度的竞争力。

Combined with standard mathematical model for evaluating quality of deploying results, a new high-performance parallel algorithm for source pencils＇ deployment was obtained by using parallel plant growth simulation algorithm which was completely parallelized with CUDA execute model, and the corresponding code can run on GPU. Based on such work, several instances in various scales were used to test the new version of algorithm. The results show that, based on the advantage of old versions, the performance of new one is improved more than 500 times comparing with the CPU version, and also 30 times with the CPU plus GPU hybrid version. The computation time of new version is less than ten minutes for the irradiator of which the activity is lessthan 111 PBq. For a single GTX275 GPU, the version is no more than 167 PBq as well as the 25 minutes, and for multiple GPUs, the power can version of algorithm running on GPU can satisfy deployment of any domestic irradiator, and it is of maximum computing power of new computation time is no more than be improved more. Overall, the new the requirement of source pencils high competitiveness.