Antoine Pedron, L. Lacassagne, F. Bimbard, S. Berre
{"title":"Parallelization of an ultrasound reconstruction algorithm for non destructive testing on multicore CPU and GPU","authors":"Antoine Pedron, L. Lacassagne, F. Bimbard, S. Berre","doi":"10.1109/DASIP.2011.6136904","DOIUrl":null,"url":null,"abstract":"The CIVA software platform developed by CEA-LIST offers various simulation and data processing modules dedicated to non-destructive testing (NDT). In particular, ultrasonic imaging and reconstruction tools are proposed, in the purpose of localizing echoes and identifying and sizing the detected defects. Because of the complexity of data processed, computation time is now a limitation for the optimal use of available information. In this article, we present performance results on parallelization of one computationally heavy algorithm on general purpose processors (GPP) and graphic processing units (GPU). GPU implementation makes an intensive use of atomic intrinsics. Compared to initial GPP implementation, optimized GPP implementation runs up to ×116 faster and GPU implementation up to ×631. This shows that, even with irregular workloads, combining software optimization and hardware improvements, GPU give high performance.","PeriodicalId":199500,"journal":{"name":"Proceedings of the 2011 Conference on Design & Architectures for Signal & Image Processing (DASIP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2011 Conference on Design & Architectures for Signal & Image Processing (DASIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DASIP.2011.6136904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The CIVA software platform developed by CEA-LIST offers various simulation and data processing modules dedicated to non-destructive testing (NDT). In particular, ultrasonic imaging and reconstruction tools are proposed, in the purpose of localizing echoes and identifying and sizing the detected defects. Because of the complexity of data processed, computation time is now a limitation for the optimal use of available information. In this article, we present performance results on parallelization of one computationally heavy algorithm on general purpose processors (GPP) and graphic processing units (GPU). GPU implementation makes an intensive use of atomic intrinsics. Compared to initial GPP implementation, optimized GPP implementation runs up to ×116 faster and GPU implementation up to ×631. This shows that, even with irregular workloads, combining software optimization and hardware improvements, GPU give high performance.