{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T05:09:07Z","timestamp":1782450547215,"version":"3.54.5"},"reference-count":71,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872423"],"award-info":[{"award-number":["61872423"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Nanjing University","award":["NY221094"],"award-info":[{"award-number":["NY221094"]}]},{"name":"Startup Foundation for Introducing Talent of Nanjing University","award":["NY221023"],"award-info":[{"award-number":["NY221023"]}]},{"name":"Startup Foundation for Introducing Talent of Nanjing University","award":["NY222084"],"award-info":[{"award-number":["NY222084"]}]},{"name":"Natural Science Foundation of Jiangsu Higher Education Institution of China","award":["22KJB510008"],"award-info":[{"award-number":["22KJB510008"]}]},{"name":"China Telecom Corporation Limited Jiangsu Branch Intelligent Cloud-Network Operation Center Lingxiao","award":["25JSCWYF5009"],"award-info":[{"award-number":["25JSCWYF5009"]}]},{"name":"Postgraduate Research"},{"name":"Practice Innovation Program of Jiangsu Province","award":["KYCX20_0764"],"award-info":[{"award-number":["KYCX20_0764"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Parallel Distrib. Syst."],"published-print":{"date-parts":[[2025,8]]},"DOI":"10.1109\/tpds.2025.3577796","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T17:36:30Z","timestamp":1749490590000},"page":"1591-1607","source":"Crossref","is-referenced-by-count":1,"title":["ISACPP: Interference-Aware Scheduling Approach for Deep Learning Training Workloads Based on Co-Location Performance Prediction"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4688-115X","authenticated-orcid":false,"given":"Zijie","family":"Liu","sequence":"first","affiliation":[{"name":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6940-7453","authenticated-orcid":false,"given":"Yi","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Can","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Hu","sequence":"additional","affiliation":[{"name":"Jiangsu Cable Television Research Institute, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6400-246X","authenticated-orcid":false,"given":"Rongguo","family":"Fu","sequence":"additional","affiliation":[{"name":"Jiangsu Earthquake Agency, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6080-6151","authenticated-orcid":false,"given":"Dengyin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3059968"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-024-02443-6"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2021.03.012"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403104"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2890784"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2523616.2523633"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3190508.3190517"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3341301.3359642"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JSYST.2021.3129974"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3138825"},{"key":"ref13","first-page":"533","article-title":"AntMan: Dynamic scaling on GPU clusters for deep learning","volume-title":"Proc. 14th USENIX Symp. Operating Syst. Des. Implementation","author":"Xiao"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3544216.3544224"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2023.3293835"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCC.2023.3336540"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3136245"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3079202"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CCGrid54584.2022.00079"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3581784.3607060"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2021.3139607"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2022.3202529"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IISWC47752.2019.9042047"},{"key":"ref24","first-page":"1","article-title":"Characterization and prediction of deep learning workloads in large-scale GPU datacenters","volume-title":"Proc. Int. Conf. High Perform. Comput. Netw. Storage Anal.","author":"Hu"},{"key":"ref25","first-page":"945","article-title":"MLaaS in the wild: Workload analysis and scheduling in Large-Scale heterogeneous GPU clusters","volume-title":"Proc. 19th USENIX Symp. Netw. Syst. Des. Implementation","author":"Weng"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-32041-5_16"},{"key":"ref27","first-page":"947","article-title":"Analysis of Large-ScaleMulti-TenantGPU clusters for DNN training workloads","volume-title":"Proc. 2019 USENIX Annu. Tech. Conf.","author":"Jeon"},{"key":"ref28","article-title":"Synergy: Resource sensitive DNN scheduling in multi-tenant clusters","author":"Mohan","year":"2021"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2023.3242200"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/s21061938"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE-SEIP58684.2023.00039"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref34","article-title":"SqueezeNet: Alexnet-level accuracy with 50x fewer parameters and$< $< 0.5 MB model size","author":"Iandola","year":"2016"},{"key":"ref35","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00716"},{"key":"ref37","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.4324\/9781410605337-29"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.5555\/3298023.3298188"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_38"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.634"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.305"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.87"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_39"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46723-8_49"},{"key":"ref51","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018"},{"key":"ref52","article-title":"Google\u2019s neural machine translation system: Bridging the gap between human and machine translation","author":"Wu","year":"2016"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2020-1557"},{"key":"ref54","first-page":"485","article-title":"Tiresias: A GPU cluster manager for distributed deep learning","volume-title":"Proc. 16th USENIX Symp. Netw. Syst. Des. Implementation","author":"Gu"},{"key":"ref55","first-page":"167","article-title":"IOS: Inter-operator scheduler for CNN acceleration","volume-title":"Proc. Mach. Learn. Syst.","volume":"3","author":"Ding"},{"key":"ref56","first-page":"559","article-title":"Alpa: Automating inter-and Intra-Operator parallelism for distributed deep learning","volume-title":"Proc. 16th USENIX Symp. Operating Syst. Des. Implementation","author":"Zheng"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-022-00568-3"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9378252"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2020.102590"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1145\/3582080"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/IC2E.2019.00-10"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/IISWC50251.2020.00026"},{"key":"ref63","article-title":"Towards GPU utilization prediction for cloud deep learning","volume-title":"Proc. 12th USENIX Workshop Hot Topics Cloud Comput.","author":"Yeung"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/BigData55660.2022.10020212"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2024.3357715"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2023.10.022"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CLUSTER52292.2023.00034"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CLUSTER52292.2023.00009"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1145\/2499368.2451125"},{"key":"ref70","first-page":"219","article-title":"DeepDive: Transparently identifying and managing performance interference in virtualized environments","volume-title":"Proc. 2013 USENIX Annu. Tech. Conf.","author":"Novakovi\u0107"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1145\/3274808.3274820"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1145\/3458817.3476215"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2023.3235710"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/TCC.2023.3319383"}],"container-title":["IEEE Transactions on Parallel and Distributed Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/71\/11045205\/11028584.pdf?arnumber=11028584","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T06:01:41Z","timestamp":1750744901000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11028584\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8]]},"references-count":71,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tpds.2025.3577796","relation":{},"ISSN":["1045-9219","1558-2183","2161-9883"],"issn-type":[{"value":"1045-9219","type":"print"},{"value":"1558-2183","type":"electronic"},{"value":"2161-9883","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8]]}}}