{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T17:55:54Z","timestamp":1782496554926,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":50,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,6,28]],"date-time":"2026-06-28T00:00:00Z","timestamp":1782604800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"German Research Foundation (DFG)","award":["AI 117\/7-1; KE 2844\/1-1"],"award-info":[{"award-number":["AI 117\/7-1; KE 2844\/1-1"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,6,29]]},"DOI":"10.1145\/3815572.3815758","type":"proceedings-article","created":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T17:44:02Z","timestamp":1782495842000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Customized Precision for Discontinuous Galerkin Methods using Adaptive Spectral Block Floating Point"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-3959-1976","authenticated-orcid":false,"given":"Shivam","family":"Sundriyal","sequence":"first","affiliation":[{"name":"Chair of Scientific Computing, University of Bayreuth, Bayreuth, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7205-1357","authenticated-orcid":false,"given":"Markus","family":"B\u00fcttner","sequence":"additional","affiliation":[{"name":"Chair of Scientific Computing, University of Bayreuth, Bayreuth, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5088-0267","authenticated-orcid":false,"given":"Tobias","family":"Kenter","sequence":"additional","affiliation":[{"name":"Paderborn Center for Parallel Computing, Paderborn University, Paderborn, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1061-3084","authenticated-orcid":false,"given":"Vadym","family":"Aizinger","sequence":"additional","affiliation":[{"name":"Chair of Scientific Computing, University of Bayreuth, Bayreuth, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,28]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","unstructured":"Ayon Basumallik Darius Bunandar Nicholas Dronen Nicholas Harris Ludmila Levkova Calvin McCarter Lakshmi Nair David Walter and David Widemann. 2022. Adaptive Block Floating-Point for Analog Deep Learning Hardware. arXiv:2205.06287 [cs.LG] doi:10.48550\/arXiv.2205.06287","DOI":"10.48550\/arXiv.2205.06287"},{"key":"e_1_3_2_1_2_1","volume-title":"Chebyshev and Fourier Spectral Methods (2nd rev. ed.)","author":"Boyd John P.","unstructured":"John P. Boyd. 2001. Chebyshev and Fourier Spectral Methods (2nd rev. ed.). Dover Publications, Mineola, NY, USA."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3659914.3659925"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-025-07063-7"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30726-6"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1090\/S0025-5718-1989-0983311-4"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1006\/jcph.1998.5892"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3765616"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","unstructured":"Zhe Dai Liang Deng Yueqing Wang Fang Wang Ming Li and Jian Zhang. 2022. Performance Optimization and Analysis of the Unstructured Discontinuous Galerkin Solver on Multi-Core and Many-Core Architectures. In 2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor Cloud & Big Data Systems & Application (HPCC\/DSS\/SmartCity\/DependSys). IEEE Piscataway NJ USA 993\u2013999. doi:10.1109\/HPCC-DSS-SmartCity-DependSys57074.2022.00158","DOI":"10.1109\/HPCC-DSS-SmartCity-DependSys57074.2022.00158"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-42808-1"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2020.101285"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511546792"},{"key":"e_1_3_2_1_13_1","volume-title":"Garnett (Eds.)","volume":"31","author":"Drumond Mario","year":"2018","unstructured":"Mario Drumond, Tao Lin, Martin Jaggi, and Babak Falsafi. 2018. Training DNNs with Hybrid Block Floating Point. In Advances in Neural Information Processing Systems, S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi, and R. Garnett (Eds.), Vol. 31. Curran Associates, Inc., Red Hook, NY, USA, 451\u2013461."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPCSim.2016.7568318"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13137-025-00267-2"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3592979.3593407"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/FPL.2013.6645508"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.14529\/jsfi170206"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/SC.2018.00050"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-72067-8"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.2017.0144"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780198528692.001.0001"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3468267.3470617"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1137\/23M1581819"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3458817.3476171"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3325864"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVLSI.2019.2913958"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPSW.2018.00091"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPEC67600.2025.11196461"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","unstructured":"Marc Marot-Lassauzaie and Michael Bader. 2025. Mixed-Precision in High-Order Methods: the Impact of Floating-Point Precision on the ADER-DG Algorithm. arXiv:2504.06889 [math.NA] doi:10.48550\/arXiv.2504.06889","DOI":"10.48550\/arXiv.2504.06889"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1710.03740"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cageo.2016.03.008"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2016.07.001"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS45731.2020.9180771"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3635035.3635046"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAU.1970.1162085"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9991(84)90128-1"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3592979.3593419"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/78.752605"},{"key":"e_1_3_2_1_40_1","volume-title":"Technical Report LA-UR-73-479. Los Alamos Scientific Laboratory","author":"Reed William H.","year":"1973","unstructured":"William H. Reed and T. R. Hill. 1973. Triangular mesh methods for the neutron transport equation. Technical Report LA-UR-73-479. Los Alamos Scientific Laboratory, Los Alamos, NM, USA."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPEC49654.2021.9622841"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1137\/18M1185399"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPEC67600.2025.11196195"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.2514\/6.2020-2922"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i20.35407"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/1498765.1498785"},{"key":"e_1_3_2_1_47_1","unstructured":"Yongqi Xu Yujian Lee Gao Yi Bosheng Liu Yucong Chen Peng Liu Jigang Wu Xiaoming Chen and Yinhe Han. 2024. BitQ: Tailoring Block Floating Point Precision for Improved DNN Efficiency on Resource-Constrained Devices. arXiv:2409.17093 [cs.CV] https:\/\/arxiv.org\/abs\/2409.17093"},{"key":"e_1_3_2_1_48_1","volume-title":"Proceedings of the 39th International Conference on Machine Learning (Proceedings of Machine Learning Research","volume":"25500","author":"Yeh Thomas","year":"2022","unstructured":"Thomas Yeh, Max Sterner, Zerlina Lai, Brandon Chuang, and Alexander Ihler. 2022. Be Like Water: Adaptive Floating Point for Machine Learning. In Proceedings of the 39th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 162). PMLR, Baltimore, MD, USA, 25490\u201325500. https:\/\/proceedings.mlr.press\/v162\/yeh22a.html"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA53966.2022.00067"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","unstructured":"Daniel Zint Roberto Grosso Vadym Aizinger Sara Faghih-Naini Sebastian Kuckuk and Harald K\u00d6stler. 2022. Automatic Generation of Load-Balancing-Aware Block-Structured Grids for Complex Ocean Domains. doi:10.5281\/zenodo.6562440","DOI":"10.5281\/zenodo.6562440"}],"event":{"name":"PASC '26: Platform for Advanced Scientific Computing Conference","location":"Bern Switzerland","acronym":"PASC '26","sponsor":["SIGHPC ACM Special Interest Group on High Performance Computing, Special Interest Group on High Performance Computing"]},"container-title":["Proceedings of the Platform for Advanced Scientific Computing Conference"],"original-title":[],"deposited":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T17:44:06Z","timestamp":1782495846000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3815572.3815758"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,28]]},"references-count":50,"alternative-id":["10.1145\/3815572.3815758","10.1145\/3815572"],"URL":"https:\/\/doi.org\/10.1145\/3815572.3815758","relation":{},"subject":[],"published":{"date-parts":[[2026,6,28]]},"assertion":[{"value":"2026-06-28","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}