{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T19:43:52Z","timestamp":1781120632711,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":26,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,8]]},"DOI":"10.1145\/3721145.3725757","type":"proceedings-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T12:57:17Z","timestamp":1755867437000},"page":"884-894","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["ORA: Job Runtime Prediction for High-Performance Computing Platforms Using the Online Retrieval-Augmented Language Model"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6404-369X","authenticated-orcid":false,"given":"Hongyi","family":"Liu","sequence":"first","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7693-2950","authenticated-orcid":false,"given":"Yinping","family":"Ma","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3462-5324","authenticated-orcid":false,"given":"Xiaosong","family":"Huang","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9500-4489","authenticated-orcid":false,"given":"Lingzhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5946-9829","authenticated-orcid":false,"given":"Tong","family":"Jia","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China and National Key Laboratory of Data Space Technology and System, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6278-2357","authenticated-orcid":false,"given":"Ying","family":"Li","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"e_1_3_3_1_2_2","unstructured":"2025. National Partnership for Advanced Computational Infrastructure. https:\/\/www.nsf.gov\/awardsearch\/showAward?AWD_ID=9619020&HistoricalAwards=false."},{"key":"e_1_3_3_1_3_2","unstructured":"2025. National Partnership for Advanced Computational Infrastructure. https:\/\/aliyun.com."},{"key":"e_1_3_3_1_4_2","unstructured":"2025. ORA. https:\/\/github.com\/lhysgithub\/ORA."},{"key":"e_1_3_3_1_5_2","unstructured":"2025. PDC Center for High Performance Computing. https:\/\/www.pdc.kth.se."},{"key":"e_1_3_3_1_6_2","unstructured":"Angels Balaguer Vinamra Benara Renato\u00a0Luiz de Freitas\u00a0Cunha Roberto de\u00a0M Estev\u00e3o\u00a0Filho Todd Hendry Daniel Holstein Jennifer Marsman Nick Mecklenburg Sara Malvar Leonardo\u00a0O Nunes et\u00a0al. 2024. RAG vs fine-tuning: Pipelines tradeoffs and a case study on agriculture. arXiv e-prints (2024) arXiv\u20132401."},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"crossref","unstructured":"Fengxian Chen. 2023. Job runtime prediction of HPC cluster based on PC-Transformer. The Journal of Supercomputing 79 17 (2023) 20208\u201320234.","DOI":"10.1007\/s11227-023-05470-2"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3407947.3407968"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"Hyunjoon Cheon Jinseung Ryu Jaecheol Ryou Chan\u00a0Yeol Park and Yo-Sub Han. 2023. ARED: automata-based runtime estimation for distributed systems using deep learning. Cluster Computing 26 5 (2023) 2629\u20132641.","DOI":"10.1007\/s10586-021-03272-w"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"crossref","unstructured":"Renato\u00a0LF Cunha Eduardo\u00a0R Rodrigues Leonardo\u00a0P Tizzei and Marco\u00a0AS Netto. 2017. Job placement advisor based on turnaround predictions for HPC hybrid clouds. Future Generation Computer Systems 67 (2017) 35\u201346.","DOI":"10.1016\/j.future.2016.08.010"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.5555\/3571885.3571916"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/CLUSTER.2017.11"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"crossref","unstructured":"Dror\u00a0G Feitelson Dan Tsafrir and David Krakov. 2014. Experience with using the parallel workloads archive. J. Parallel and Distrib. Comput. 74 10 (2014) 2967\u20132982.","DOI":"10.1016\/j.jpdc.2014.06.013"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/2807591.2807646"},{"key":"e_1_3_3_1_15_2","unstructured":"Guolin Ke Qi Meng Thomas Finley Taifeng Wang Wei Chen Weidong Ma Qiwei Ye and Tie-Yan Liu. 2017. Lightgbm: A highly efficient gradient boosting decision tree. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Sheng-Chieh Lin Minghan Li and Jimmy Lin. 2023. Aggretriever: A simple approach to aggregate textual representations for robust dense passage retrieval. Transactions of the Association for Computational Linguistics 11 (2023) 436\u2013452.","DOI":"10.1162\/tacl_a_00556"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"crossref","unstructured":"Chun Liu Baoqing Wang and Yuqiang Li. 2023. Dialog generation model based on variational Bayesian knowledge retrieval method. Neurocomputing 561 (2023) 126878.","DOI":"10.1016\/j.neucom.2023.126878"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"crossref","unstructured":"Ju-Won Park and Eunhye Kim. 2017. Runtime prediction of parallel applications with workload-aware clustering. The Journal of Supercomputing 73 11 (2017) 4635\u20134651.","DOI":"10.1007\/s11227-017-2038-2"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/664\/6\/062050"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"Stephen Robertson Hugo Zaragoza et\u00a0al. 2009. The probabilistic relevance framework: BM25 and beyond. Foundations and Trends\u00ae in Information Retrieval 3 4 (2009) 333\u2013389.","DOI":"10.1561\/1500000019"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"crossref","unstructured":"Dan Tsafrir Yoav Etsion and Dror\u00a0G Feitelson. 2007. Backfilling using system-generated predictions rather than user runtime estimates. IEEE Transactions on Parallel and Distributed Systems 18 6 (2007) 789\u2013803.","DOI":"10.1109\/TPDS.2007.70606"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/CLUSTR.2007.4629218"},{"key":"e_1_3_3_1_23_2","unstructured":"Tong Ye Lingfei Wu Tengfei Ma Xuhong Zhang Yangkai Du Peiyu Liu Shouling Ji and Wenhai Wang. 2023. Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2305.11074 (2023)."},{"key":"e_1_3_3_1_24_2","unstructured":"Xunjian Yin Baizhou Huang and Xiaojun Wan. 2023. ALCUNA: Large language models meet new knowledge. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2310.14820 (2023)."},{"key":"e_1_3_3_1_25_2","unstructured":"Ori Yoran Tomer Wolfson Ori Ram and Jonathan Berant. 2023. Making retrieval-augmented language models robust to irrelevant context. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2310.01558 (2023)."},{"key":"e_1_3_3_1_26_2","unstructured":"Wenhao Yu Hongming Zhang Xiaoman Pan Kaixin Ma Hongwei Wang and Dong Yu. 2023. Chain-of-note: Enhancing robustness in retrieval-augmented language models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2311.09210 (2023)."},{"key":"e_1_3_3_1_27_2","unstructured":"Shuyan Zhou Uri Alon Frank\u00a0F Xu Zhiruo Wang Zhengbao Jiang and Graham Neubig. 2022. Docprompting: Generating code by retrieving the docs. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2207.05987 (2022)."}],"event":{"name":"ICS '25: 2025 International Conference on Supercomputing","location":"Salt Lake City USA","acronym":"ICS '25","sponsor":["SIGARCH ACM Special Interest Group on Computer Architecture"]},"container-title":["Proceedings of the 39th ACM International Conference on Supercomputing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3721145.3725757","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T12:58:30Z","timestamp":1755867510000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3721145.3725757"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,8]]},"references-count":26,"alternative-id":["10.1145\/3721145.3725757","10.1145\/3721145"],"URL":"https:\/\/doi.org\/10.1145\/3721145.3725757","relation":{},"subject":[],"published":{"date-parts":[[2025,6,8]]},"assertion":[{"value":"2025-08-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}