{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T17:13:07Z","timestamp":1770743587513,"version":"3.49.0"},"reference-count":41,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"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":["U22A2021"],"award-info":[{"award-number":["U22A2021"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U23A20313"],"award-info":[{"award-number":["U23A20313"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U24A20245"],"award-info":[{"award-number":["U24A20245"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62132022"],"award-info":[{"award-number":["62132022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovation Project of Guangxi Graduate Education"},{"name":"Science and Technology Innovation Program of Hunan Province","award":["2024RC1005"],"award-info":[{"award-number":["2024RC1005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput."],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1109\/tc.2025.3525604","type":"journal-article","created":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T19:23:05Z","timestamp":1736191385000},"page":"1362-1376","source":"Crossref","is-referenced-by-count":3,"title":["Asynchronous Control Based Aggregation Transport Protocol for Distributed Deep Learning"],"prefix":"10.1109","volume":"74","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8087-6333","authenticated-orcid":false,"given":"Jin","family":"Ye","sequence":"first","affiliation":[{"name":"School of Computer and Electronic Information, Guangxi University, Nanning, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6921-191X","authenticated-orcid":false,"given":"Yajun","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer and Electronic Information, Guangxi University, Nanning, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4335-8742","authenticated-orcid":false,"given":"Yijun","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9677-2368","authenticated-orcid":false,"given":"Zhaoyi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7578-4490","authenticated-orcid":false,"given":"Jiawei","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref2","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Brown","year":"2020"},{"key":"ref3","first-page":"645","article-title":"Neural adaptive content-aware internet video delivery","volume-title":"Proc. USENIX OSDI","author":"Yeo","year":"2018"},{"key":"ref4","article-title":"Horovod: fast and easy distributed deep learning in TensorFlow","author":"Sergeev","year":"2018"},{"key":"ref5","first-page":"463","article-title":"A unified architecture for accelerating distributed DNN training in heterogeneous GPU\/CPU clusters","volume-title":"Proc. USENIX OSDI","author":"Jiang","year":"2020"},{"key":"ref6","first-page":"673","article-title":"Whale: Efficient giant model training over heterogeneous GPUs","volume-title":"Proc. USENIX ATC","author":"Jia","year":"2022"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3341301.3359646"},{"key":"ref8","first-page":"785","article-title":"Scaling distributed machine learning with in-network aggregation","volume-title":"Proc. USENIX NSDI","author":"Sapio","year":"2021"},{"key":"ref9","first-page":"741","article-title":"ATP: In-network aggregation for multi-tenant learning","volume-title":"Proc. USENIX NSDI","author":"Lao","year":"2021"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3458817.3476178"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796688"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3132747.3132764"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2640087.2644155"},{"key":"ref14","first-page":"829","article-title":"In-network aggregation for shared machine learning clusters","volume-title":"Proc. Mach. Learn. Syst.","volume":"3","author":"Gebara","year":"2021"},{"key":"ref15","article-title":"Efficient data-plane memory scheduling for in-network aggregation","author":"Wang","year":"2022"},{"key":"ref16","first-page":"1","article-title":"The addition of explicit congestion notification (ECN) to ip","author":"Floyd","year":"2001"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/1851182.1851192"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref19","first-page":"1106","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"25","author":"Krizhevsky","year":"2012"},{"key":"ref20","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"ref21","first-page":"7","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"issue":"14","key":"ref22","first-page":"527","article-title":"Network simulations with the ns-3 simulator","volume":"14","author":"Henderson","year":"2008","journal-title":"SIGCOMM Demonstration"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CLUSTER49012.2020.00025"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3152434.3152461"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/IWQoS57198.2023.10188783"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3552326.3587436"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3452296.3472904"},{"key":"ref28","first-page":"5788","article-title":"Hierarchical channel-spatial encoding for communication-efficient collaborative learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Zhou","year":"2022"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3489517.3530417"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i4.16462"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3503221.3508399"},{"key":"ref32","first-page":"23274","article-title":"DRAGONN: Distributed randomized approximate gradients of neural networks","volume-title":"Proc. ACM ICML","author":"Wang","year":"2022"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS51616.2021.00060"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796752"},{"key":"ref35","first-page":"56","article-title":"Logical\/physical topology-aware collective communication in deep learning training","volume-title":"Proc. IEEE HPCA","author":"Sanghoon","year":"2023"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488810"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM53939.2023.10229053"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2022.3228733"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-022-04422-6"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3545008.3545010"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2021.3063180"}],"container-title":["IEEE Transactions on Computers"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/12\/10924434\/10827826.pdf?arnumber=10827826","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,13]],"date-time":"2025-03-13T06:08:04Z","timestamp":1741846084000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10827826\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":41,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tc.2025.3525604","relation":{},"ISSN":["0018-9340","1557-9956","2326-3814"],"issn-type":[{"value":"0018-9340","type":"print"},{"value":"1557-9956","type":"electronic"},{"value":"2326-3814","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4]]}}}