{"title":"A C++ class supporting state-deficient adjoint state methods","authors":"M. Enríquez","doi":"10.1145/1347787.1347805","DOIUrl":null,"url":null,"abstract":"The adjoint-state method is widely used for computing gradients in simulation-driven optimization problems. The adjoint-state evolution equation requires access to the entire history of the system states. There are instances, however, where the required state for the adjoint-state evolution is not readily accessible. This poster introduces a C++ class, StateHistory, to support multiple solutions to this problem. Derived StateHistory classes implement a (simulation) time-altering function and data-access functions, which can be used in tandem to access the entire state history. These ideas were implemented in the context of TSOpt, a time-stepping library for simulation-driven optimization algorithms. Copyright is held by author/owner(s) Tapia'07, October 14-17, 2007, Lake Buena Vista, Florida, USA ACM 978-1-59593-866-4/07/0010","PeriodicalId":326471,"journal":{"name":"Richard Tapia Celebration of Diversity in Computing Conference","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Richard Tapia Celebration of Diversity in Computing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1347787.1347805","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The adjoint-state method is widely used for computing gradients in simulation-driven optimization problems. The adjoint-state evolution equation requires access to the entire history of the system states. There are instances, however, where the required state for the adjoint-state evolution is not readily accessible. This poster introduces a C++ class, StateHistory, to support multiple solutions to this problem. Derived StateHistory classes implement a (simulation) time-altering function and data-access functions, which can be used in tandem to access the entire state history. These ideas were implemented in the context of TSOpt, a time-stepping library for simulation-driven optimization algorithms. Copyright is held by author/owner(s) Tapia'07, October 14-17, 2007, Lake Buena Vista, Florida, USA ACM 978-1-59593-866-4/07/0010