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Simul."],"published-print":{"date-parts":[[2025,7,31]]},"abstract":"<jats:p>Simulation cloning is a technique in which cloned simulations whose state spaces differ partially from their parent simulation due to intervening events are spawned at runtime and concurrently advanced. It is a powerful method to carry out what-if analysis by speculatively exploring and evaluating the impact of various permutations of intervening cascade of events. Due to the exponential growth in the number of possible clones even for a small number of distinct intervening events, the practical efficacy of the approach is often severely limited by the maximum available memory of the computing host. In this paper, we introduce a novel speculative simulation cloning framework that executes a simulation cloning campaign capable of efficiently exploring an exponentially large space of clone simulations created by permutation of intervening events under a finite memory constraint. We provide a theoretical analysis of the runtime characteristics of our proposed approach and highlight its novel advantages such as memory-aware and as-long-as-needed execution. In support of our analytical findings and to demonstrate its practical feasibility, we implement a prototype of the cloning framework on a shared memory system and report its performance characteristics in the context of a heat diffusion simulation, and a power grid simulation subject to cascading disruptions from geomagnetic disturbances.<\/jats:p>","DOI":"10.1145\/3708885","type":"journal-article","created":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T04:31:52Z","timestamp":1735187512000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["SpecSims: A Scalable Speculative Tree-based Simulation Cloning Framework for Finite Memory Machines"],"prefix":"10.1145","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8423-6050","authenticated-orcid":false,"given":"Srikanth","family":"Yoginath","sequence":"first","affiliation":[{"name":"Computer Science and Mathematics, Oak Ridge National Laboratory","place":["Oak Ridge, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3245-6275","authenticated-orcid":false,"given":"Pratishtha","family":"Shukla","sequence":"additional","affiliation":[{"name":"Computational Sciences and Engineering, Oak Ridge National Laboratory","place":["Oak Ridge, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7360-2836","authenticated-orcid":false,"given":"James","family":"Nutaro","sequence":"additional","affiliation":[{"name":"Computational Sciences and Engineering, Oak Ridge National Laboratory","place":["Oak Ridge, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3233-0656","authenticated-orcid":false,"given":"Sudip","family":"Seal","sequence":"additional","affiliation":[{"name":"Computer Science and Mathematics, Oak Ridge National Laboratory","place":["Oak Ridge, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,5,16]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/PADS.2005.6"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/SIMSYM.2003.1192814"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/1113316.1113318"},{"key":"e_1_3_1_5_2","volume-title":"Large-scale Simulation: Models, Algorithms, and Applications","author":"Chen Dan","year":"2012","unstructured":"Dan Chen, Lizhe Wang, and Jingying Chen. 2012. 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