{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T03:42:15Z","timestamp":1725594135250},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1109\/globecom38437.2019.9013361","type":"proceedings-article","created":{"date-parts":[[2020,2,28]],"date-time":"2020-02-28T04:59:24Z","timestamp":1582865964000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["Topology-Aware Job Scheduling for Machine Learning Cluster"],"prefix":"10.1109","author":[{"given":"Jingyuan","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huibin","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enting","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Song","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Scaling distributed machine learning with the parameter server","author":"m l","year":"0","journal-title":"Proc of OSDI 2014"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2018.2843326"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2018.2829886"},{"key":"ref13","article-title":"Large-scale cluster management at google with borg","author":"verma","year":"0","journal-title":"Proc EuroSys 2015"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2523616.2523633"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2019.2931716"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2018.8486422"},{"key":"ref17","article-title":"Gandiva: Introspective cluster scheduling for deep learning","author":"xiao","year":"0","journal-title":"Proc OSDI 2018"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/MCC.2018.1081060"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2018.2805718"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/0743-7315(90)90004-9"},{"key":"ref4","article-title":"Optimus: An efficient dynamic resource scheduler for deep learning clusters","author":"peng","year":"0","journal-title":"Proceedings of Eurosys 2018"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2987550.2987563"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGCN.2019.2893712"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2018.00060"},{"key":"ref5","article-title":"Tensorflow: A system for large-scale machine learning","author":"m a","year":"2016","journal-title":"CoRR"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00028"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2018.2857922"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2018.2813333"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2018.2871449"},{"journal-title":"Google 2017 google cloud prediction api documentation","year":"2017","key":"ref1"},{"journal-title":"Multi-tenant gpu clusters for deep learning workloads Analysis and implications","year":"2018","author":"jeon","key":"ref20"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3267809.3267840"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3126908.3126933"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/2987550.2987554"},{"key":"ref26","article-title":"Reinforcement learning-based adaptive resource management of differentiated services in geo-distributed data centers","author":"zhou","year":"0","journal-title":"IEEE\/ACM IWQoS 2017"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2015.2472014"}],"event":{"name":"GLOBECOM 2019 - 2019 IEEE Global Communications Conference","start":{"date-parts":[[2019,12,9]]},"location":"Waikoloa, HI, USA","end":{"date-parts":[[2019,12,13]]}},"container-title":["2019 IEEE Global Communications Conference (GLOBECOM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8968653\/9013108\/09013361.pdf?arnumber=9013361","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T17:55:08Z","timestamp":1658080508000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9013361\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/globecom38437.2019.9013361","relation":{},"subject":[],"published":{"date-parts":[[2019,12]]}}}