{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T22:40:13Z","timestamp":1752532813230,"version":"3.41.2"},"reference-count":2,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"U.S. Department of Energy by Lawrence Livermore National Laboratory","award":["DE-AC52-07NA27344"],"award-info":[{"award-number":["DE-AC52-07NA27344"]}]},{"name":"Neither the United States government nor Lawrence Livermore National Security, LLC"},{"name":"United States government or Lawrence Livermore National Security, LLC"},{"name":"United States government"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Math. Softw."],"published-print":{"date-parts":[[2021,6,30]]},"abstract":"<jats:p>The article by Flegar et\u00a0al. titled \u201cAdaptive Precision Block-Jacobi for High Performance Preconditioning in the Ginkgo Linear Algebra Software\u201d presents a novel, practical implementation of an adaptive precision block-Jacobi preconditioner. Performance results using state-of-the-art GPU architectures for the block-Jacobi preconditioner generation and application demonstrate the practical usability of the method, compared to a traditional full-precision block-Jacobi preconditioner. A production-ready implementation is provided in the Ginkgo numerical linear algebra library.<\/jats:p>\n          <jats:p>In this report, the Ginkgo library is reinstalled and performance results are generated to perform a comparison to the original results when using Ginkgo\u2019s Conjugate Gradient solver with either the full or the adaptive precision block-Jacobi preconditioner for a suite of test problems on an NVIDIA GPU accelerator. After completing this process, the published results are deemed reproducible.<\/jats:p>","DOI":"10.1145\/3446000","type":"journal-article","created":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T12:04:30Z","timestamp":1617278670000},"page":"1-4","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Replicated Computational Results (RCR) Report for \u201cAdaptive Precision Block-Jacobi for High Performance Preconditioning in the Ginkgo Linear Algebra Software\u201d"],"prefix":"10.1145","volume":"47","author":[{"given":"Sarah","family":"Osborn","sequence":"first","affiliation":[{"name":"Lawrence Livermore National Laboratory, Livermore, CA"}]}],"member":"320","published-online":{"date-parts":[[2021,4]]},"reference":[{"volume-title":"Retrieved","year":"2020","key":"e_1_2_1_1_1","unstructured":"GitHub. n.d. Instructions to Reproduce Experiments. Retrieved October 23, 2020 from https:\/\/github.com\/ginkgo-project\/ginkgo\/blob\/2019toms-adaptive-bj-solver\/Reproduce_Experiments.md."},{"key":"e_1_2_1_2_1","first-page":"1","article-title":"Adaptive precision block-Jacobi for high performance preconditioning in the Ginkgo linear algebra software","volume":"1","author":"Flegar Goran","year":"2020","unstructured":"Goran Flegar, Hartwig Anzt, Terry Cojean, and Enrique S. Quintana-Orti. 2020. Adaptive precision block-Jacobi for high performance preconditioning in the Ginkgo linear algebra software. ACM Transactions on Mathematical Software 1, 1 (Aug. 2020), Article 1, 27 pages.","journal-title":"ACM Transactions on Mathematical Software"}],"container-title":["ACM Transactions on Mathematical Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3446000","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3446000","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T22:26:44Z","timestamp":1752532004000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3446000"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4]]},"references-count":2,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,6,30]]}},"alternative-id":["10.1145\/3446000"],"URL":"https:\/\/doi.org\/10.1145\/3446000","relation":{},"ISSN":["0098-3500","1557-7295"],"issn-type":[{"type":"print","value":"0098-3500"},{"type":"electronic","value":"1557-7295"}],"subject":[],"published":{"date-parts":[[2021,4]]},"assertion":[{"value":"2020-11-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-12-01","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-04-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}