{"title":"Fast-QSGS:用于粒状无序介质结构生成的 GPU 加速程序","authors":"Guang Yang, Tong Liu, Xukang Lu, Moran Wang","doi":"10.1016/j.cpc.2024.109241","DOIUrl":null,"url":null,"abstract":"<div><p>We present Fast-QSGS, a GPU-accelerated program for granular disordered media generation. Based on vectorization, Fast-QSGS is accelerated by modern GPU thanks to the NumPy-compatible API provided by CuPy. We also introduce a variable growth probability function and seed spacing control to improve the speed and accuracy of the original QSGS method. Computational performance benchmarks are conducted on both consumer-grade and professional-grade GPUs. Generation of disordered media of size 400<sup>3</sup> can be completed in 30 s on A100 and 110 s on RTX4060, achieving a speedup of over 400 compared with the serial version. Physical benchmarks on the reconstruction of Fontainebleau sandstone and hydrated cement are conducted. Our results demonstrate that the permeability of the reconstructed Fontainebleau sandstone falls within the range of experimental values. Additionally, the average relative error of the volume fraction of the unhydrated cement and capillary porosity of hydrated cement is 1.9 % and 3.4 % compared with Powers’ law, respectively.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":null,"pages":null},"PeriodicalIF":7.2000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast-QSGS: A GPU accelerated program for structure generation of granular disordered media\",\"authors\":\"Guang Yang, Tong Liu, Xukang Lu, Moran Wang\",\"doi\":\"10.1016/j.cpc.2024.109241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We present Fast-QSGS, a GPU-accelerated program for granular disordered media generation. Based on vectorization, Fast-QSGS is accelerated by modern GPU thanks to the NumPy-compatible API provided by CuPy. We also introduce a variable growth probability function and seed spacing control to improve the speed and accuracy of the original QSGS method. Computational performance benchmarks are conducted on both consumer-grade and professional-grade GPUs. Generation of disordered media of size 400<sup>3</sup> can be completed in 30 s on A100 and 110 s on RTX4060, achieving a speedup of over 400 compared with the serial version. Physical benchmarks on the reconstruction of Fontainebleau sandstone and hydrated cement are conducted. Our results demonstrate that the permeability of the reconstructed Fontainebleau sandstone falls within the range of experimental values. Additionally, the average relative error of the volume fraction of the unhydrated cement and capillary porosity of hydrated cement is 1.9 % and 3.4 % compared with Powers’ law, respectively.</p></div>\",\"PeriodicalId\":285,\"journal\":{\"name\":\"Computer Physics Communications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.2000,\"publicationDate\":\"2024-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Physics Communications\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0010465524001644\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Physics Communications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010465524001644","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Fast-QSGS: A GPU accelerated program for structure generation of granular disordered media
We present Fast-QSGS, a GPU-accelerated program for granular disordered media generation. Based on vectorization, Fast-QSGS is accelerated by modern GPU thanks to the NumPy-compatible API provided by CuPy. We also introduce a variable growth probability function and seed spacing control to improve the speed and accuracy of the original QSGS method. Computational performance benchmarks are conducted on both consumer-grade and professional-grade GPUs. Generation of disordered media of size 4003 can be completed in 30 s on A100 and 110 s on RTX4060, achieving a speedup of over 400 compared with the serial version. Physical benchmarks on the reconstruction of Fontainebleau sandstone and hydrated cement are conducted. Our results demonstrate that the permeability of the reconstructed Fontainebleau sandstone falls within the range of experimental values. Additionally, the average relative error of the volume fraction of the unhydrated cement and capillary porosity of hydrated cement is 1.9 % and 3.4 % compared with Powers’ law, respectively.
期刊介绍:
The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper.
Computer Programs in Physics (CPiP)
These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged.
Computational Physics Papers (CP)
These are research papers in, but are not limited to, the following themes across computational physics and related disciplines.
mathematical and numerical methods and algorithms;
computational models including those associated with the design, control and analysis of experiments; and
algebraic computation.
Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.