{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T17:58:32Z","timestamp":1770227912094,"version":"3.49.0"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"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":["61902366"],"award-info":[{"award-number":["61902366"]}],"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":["U22A2068"],"award-info":[{"award-number":["U22A2068"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["202042008"],"award-info":[{"award-number":["202042008"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program of China","award":["2021YFF0704000"],"award-info":[{"award-number":["2021YFF0704000"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902365"],"award-info":[{"award-number":["61902365"]}],"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":["62072083"],"award-info":[{"award-number":["62072083"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1815412"],"award-info":[{"award-number":["CNS-1815412"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1908536"],"award-info":[{"award-number":["CNS-1908536"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Computer Department of Ocean University of China","award":["CSZS2022004"],"award-info":[{"award-number":["CSZS2022004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Parallel Distrib. Syst."],"published-print":{"date-parts":[[2023,2,1]]},"DOI":"10.1109\/tpds.2022.3228733","type":"journal-article","created":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T19:35:31Z","timestamp":1670960131000},"page":"687-703","source":"Crossref","is-referenced-by-count":15,"title":["FSP: Towards Flexible Synchronous Parallel Frameworks for Distributed Machine Learning"],"prefix":"10.1109","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1812-1068","authenticated-orcid":false,"given":"Zhigang","family":"Wang","sequence":"first","affiliation":[{"name":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"}]},{"given":"Yilei","family":"Tu","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9698-7310","authenticated-orcid":false,"given":"Ning","family":"Wang","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9017-5132","authenticated-orcid":false,"given":"Lixin","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4952-7666","authenticated-orcid":false,"given":"Jie","family":"Nie","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"}]},{"given":"Zhiqiang","family":"Wei","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7422-6254","authenticated-orcid":false,"given":"Yu","family":"Gu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3171-8889","authenticated-orcid":false,"given":"Ge","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-011-5014-9_12"},{"key":"ref2","first-page":"1463","article-title":"Starting small-learning with adaptive sample sizes","volume-title":"Proc. 33rd Int. Conf. Mach. Learn.","author":"Daneshmand"},{"key":"ref3","first-page":"1504","article-title":"Automated inference with adaptive batches","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statist.","author":"De"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623612"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390305"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1920931"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2013.158"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/79173.79181"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2806777.2806851"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CLUSTER.2012.81"},{"key":"ref11","first-page":"443","article-title":"FaaSNet: Scalable and fast provisioning of custom serverless container runtimes at Alibaba cloud function compute","volume-title":"Proc. USENIX Annu. Tech. Conf.","author":"Wang"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/2442516.2442538"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/GLOCOM.2016.7841777"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2987550.2987554"},{"key":"ref15","article-title":"Revisiting distributed synchronous SGD","author":"Pan","year":"2017"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.107846"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-022-04422-6"},{"key":"ref18","first-page":"1223","article-title":"More effective distributed ML via a stale synchronous parallel parameter server","volume-title":"Proc. 27th Annu. Conf. Neural Inf. Process. Syst.","author":"Ho"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3341620.3341625"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2020.3040601"},{"key":"ref21","first-page":"693","article-title":"HOGWILD: A lock-free approach to parallelizing stochastic gradient descent","volume-title":"Proc. 25th Annu. Conf. Neural Inf. Process. Syst.","author":"Recht"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.5555\/2685048.2685095"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS47924.2020.00052"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3492324.3494167"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737587"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TCC.2021.3102593"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-06064-w"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3127479.3128612"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015332"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.2307\/2984875"},{"key":"ref31","first-page":"495","article-title":"Efficient learning using forward-backward splitting","volume-title":"Proc. 23rd Annu. Conf. Neural Inf. Process. Syst.","author":"Duchi"},{"key":"ref32","first-page":"456","article-title":"Distributed training strategies for the structured perceptron","volume-title":"Proc. Hum. Lang. Technol.: Conf. North Amer. Chapter Assoc. Comput. Linguistics","author":"McDonald"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472805"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1029\/2020MS002298"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1137\/16M1080173"},{"issue":"3","key":"ref37","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1023\/A:1017986506241","article-title":"Accelerating em for large databases","volume":"45","author":"Thiesson","year":"2001","journal-title":"Mach. Learn."},{"key":"ref38","article-title":"Horovod: Fast and easy distributed deep learning in tensorflow","author":"Sergeev","year":"2018"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_2"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3423211.3425693"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3274808.3274828"},{"key":"ref42","first-page":"571","article-title":"Project adam: Building an efficient and scalable deep learning training system","volume-title":"Proc. 11th USENIX Symp. Oper. Syst. Des. Implementation","author":"Chilimbi"},{"key":"ref45","first-page":"3368","article-title":"Gradient coding: Avoiding stragglers in distributed learning","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Tandon"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3452773"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/HPCC\/SmartCity\/DSS.2019.00042"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3035933"},{"key":"ref49","article-title":"Straggler-robust distributed optimization in parameter-server networks","author":"Atallah","year":"2021"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2020.3046440"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/IC2E52221.2021.00035"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3187009.3177734"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2020.2974461"},{"key":"ref54","first-page":"631","article-title":"Litz: Elastic framework for high-performance distributed machine learning","volume-title":"Proc. USENIX Annu. Tech. Conf.","author":"Qiao"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3104242"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1145\/3419111.3421307"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1145\/3337821.3337828"}],"container-title":["IEEE Transactions on Parallel and Distributed Systems"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/71\/9996310\/9983509-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/71\/9996310\/09983509.pdf?arnumber=9983509","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T04:44:11Z","timestamp":1706762651000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9983509\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,1]]},"references-count":55,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tpds.2022.3228733","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":[[2023,2,1]]}}}