{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T16:48:08Z","timestamp":1765039688192,"version":"build-2065373602"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,8,12]],"date-time":"2023-08-12T00:00:00Z","timestamp":1691798400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,8,12]],"date-time":"2023-08-12T00:00:00Z","timestamp":1691798400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the Fundamental Research Funds for the Central Universities","award":["2022YQJD10"],"award-info":[{"award-number":["2022YQJD10"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1007\/s10586-023-04104-9","type":"journal-article","created":{"date-parts":[[2023,8,12]],"date-time":"2023-08-12T09:02:18Z","timestamp":1691830938000},"page":"2775-2784","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Mixtran: an efficient and fair scheduler for mixed deep learning workloads in heterogeneous GPU environments"],"prefix":"10.1007","volume":"27","author":[{"given":"Xiao","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,12]]},"reference":[{"key":"4104_CR1","doi-asserted-by":"crossref","unstructured":"LeCun,\u00a0Y., Bengio, H., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","DOI":"10.1038\/nature14539"},{"key":"4104_CR2","unstructured":"Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach. Pearson Education, Upper Saddle River (2003)"},{"key":"4104_CR3","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"4104_CR4","unstructured":"Wu, Y., Schuster, M., Chen, Z., Le, Q.V., Norouzi, M., Macherey, W., Krikun, M., Cao, Y., Gao, Q., Macherey, K.: Google\u2019s neural machine translation system: bridging the gap between human and machine translation. arXiv preprint (2016). arXiv:1609.08144"},{"key":"4104_CR5","unstructured":", W., Wu, L., Alleva, F., Droppo, J., Huang, X.: The Microsoft 2017 conversational speech recognition system. In: Proceedings of IEEE ICASSP (2017)"},{"key":"4104_CR6","unstructured":"Amodei, D., Ananthanarayanan, S., Anubhai, R., Bai, J., Zhu, Z.: DeepSpeech2: end-to-end speech recognition in English and Mandarin. In: Proceedings of the 33rd International Conference on Machine Learning, New York (2015)"},{"key":"4104_CR7","unstructured":"LibriSpeech ASR Corpus (2015). http:\/\/www.openslr.org\/12"},{"key":"4104_CR8","unstructured":"Jeon, M., Venkataraman, S., Qian, J., Phanishayee, A., Xiao, W., Fan, Y.: Multi-tenant gpu clusters for deep learning workloads: Analysis and implications (2018)"},{"key":"4104_CR9","unstructured":"Ghodsi, A., Zaharia, M., Hindman, B., Konwinski, A., Shenker, S., Stoica, I.: Dominant resource fairness: fair allocation of multiple resource types. In: Proceedings of the 8th USENIX Conference on Networked Systems Design and Implementation (NSDI 2011), pp. 323\u2013336. USENIX Association, Berkeley (2011)"},{"key":"4104_CR10","unstructured":"Gog, I., Schwarzkopf, M., Gleave, A., Watson, R., Hand, S.: Firmament: fast, centralized cluster scheduling at scale. In: 12th USENIX Symposium on Operating Systems Design and\nImplementation (2016)"},{"key":"4104_CR11","unstructured":"Grandl, R., Chowdhury, M., Akella, A., Ananthanarayanan, G.: Altruistic scheduling in multi-resource clusters. In: Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation (OSDI) (2016)"},{"key":"4104_CR12","unstructured":"Grandl, R., Kandula, S., Rao, S., Akella, A., Kulkarni, J.: Graphene: Packing and dependency-aware scheduling for data-parallel clusters. In: 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI) (2016)"},{"key":"4104_CR13","doi-asserted-by":"crossref","unstructured":"Huang, B., Boehm, M., Tian, Y., Reinwald, B., Tatikonda, S., Reiss, F.R.: Resource elasticity for large-scale machine learning. In:  Proceedings of the 2015 ACM SIGMOD International Conference on Management Data, pp. 137\u2013152. ACM, New York (2015)","DOI":"10.1145\/2723372.2749432"},{"key":"4104_CR14","unstructured":"Peng, S., Wen, Y., Ta, N., Yan, S.: Towards distributed machine learning in shared clusters: a dynamically-partitioned approach. In: 2017 IEEE International Conference on Smart Computing (SMARTCOMP) (2017)"},{"key":"4104_CR15","doi-asserted-by":"crossref","unstructured":"Zhang, H., Stafman, L., Or, A., Freedman, M.J.: Slaq: Quality-driven scheduling for distributed machine learning. In: Proceedings of the 2017 Symposium on Cloud Computing, SoCC 2017, Santa Clara (2017)","DOI":"10.1145\/3127479.3127490"},{"key":"4104_CR16","unstructured":"Gu, J., Chowdhury, M., Kang, S., Zhu, Y., Jeon, M., Qian, J., Liu, H., Guo, C.: Tiresias: a GPU cluster manager for distributed deep learning. In: 16th USENIX Symposium on Networked Systems Design and Implementation (NSDI) (2019)"},{"key":"4104_CR17","doi-asserted-by":"crossref","unstructured":"Peng, Y., Bao, Y., Chen, Y., Wu, C., Guo, C.: Optimus: an efficient dynamic resource scheduler for deep learning clusters. In: IEEE INFOCOM 2018\u2014IEEE Conference on Computer Communications (2018)","DOI":"10.1145\/3190508.3190517"},{"key":"4104_CR18","unstructured":"Xiao, W., Bhardwaj, R., Ramjee, R., Sivathanu, M., Kwatra, N., Han, Z., Patel, P., Peng, X., Zhao, H., Zhang, Q.: Gandiva: introspective cluster scheduling for deep learning. In: Proceedings of Operating Systems Design and Implementation (2018)"},{"issue":"1","key":"4104_CR19","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1145\/2898442.2898444","volume":"14","author":"B Burns","year":"2016","unstructured":"Burns, B., Grant, B., Oppenheimer, D., Brewer, E., Wilkes, J.: Borg, omega, and kubernetes: lessons learned from three container-management systems over a decade. Queue 14(1), 70\u201393 (2016). https:\/\/doi.org\/10.1145\/2898442.2898444","journal-title":"Queue"},{"key":"4104_CR20","doi-asserted-by":"crossref","unstructured":"Vavilapalli, V.K., Seth, S., Saha, B., Curino, C., O\u2019Malley, O., Radia, S., Benjaminn, R., Baldeschwieler, E., Murthy, A.C., Douglas, C.: Apache Hadoop YARN: yet another resource negotiator. In: SoCC\u201913, 1\u20133 October 2013, Santa Clara (2013)","DOI":"10.1145\/2523616.2523633"},{"key":"4104_CR21","doi-asserted-by":"crossref","unstructured":"Verma, A., Pedrosa, L., Korupolu, M., Oppenheimer, D., Tune, E., Wilkes, J.: Large-scale cluster management at Google with borg. In: 10th European Conference on Computer Systems, pp. 1\u201317 (2015)","DOI":"10.1145\/2741948.2741964"},{"key":"4104_CR22","doi-asserted-by":"crossref","unstructured":"Jalaparti, V., BodXed, P., Menache, I., Rao, S., Makarychev, K., Caesar, M.C.: Network-Aware Scheduling for Data-Parallel Jobs: Plan When You can. Association for Computing Machinery (ACM), New York (2015)","DOI":"10.1145\/2785956.2787488"},{"key":"4104_CR23","doi-asserted-by":"crossref","unstructured":"Tumanov, A., Zhu, T., Park, J.W., Kozuch, M.A., Harcholbalter, M., Ganger, G.R.: Tetrisched: global rescheduling with adaptive plan-ahead in dynamic heterogeneous clusters. In: Proceedings of 11th European Conference on Computer Systems (2016)","DOI":"10.1145\/2901318.2901355"},{"key":"4104_CR24","unstructured":"Hindman, B., Konwinski, A., Ion: Mesos: a platform for fine-grained resource sharing in the data center. In: NSDI\u201911: Proceedings of the 8th USENIX conference on Networked Systems Design and Implementation  (2013)"},{"key":"4104_CR25","unstructured":"Kingma, D.P., Welling, M.: Stochastic gradient vb and the variational auto-encoder. In :Second International Conference on Learning Representations, ICLR2014 (2014)"},{"key":"4104_CR26","unstructured":"https:\/\/github.com\/pytorch\/examples\/tree\/master\/word_language_model:Lstmtrainingonwikitext-2dataset (2017)"},{"key":"4104_CR27","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint (2015). arXiv:1511.06434"},{"key":"4104_CR28","doi-asserted-by":"crossref","unstructured":"Ausubel, L.M., Milgrom, P.: The lovely but lonely vickrey auction. In: Combinatorial Auctions. MIT, Cambridge (2006)","DOI":"10.7551\/mitpress\/9780262033428.003.0002"},{"issue":"1","key":"4104_CR29","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1017\/S0269888910000287","volume":"26","author":"Parsons Simon","year":"2011","unstructured":"Simon, P.: Algorithmic game theory. Knowl. Eng. Rev. 26(1), 71\u201372 (2011)","journal-title":"The knowledge engineering review"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-023-04104-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-023-04104-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-023-04104-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,29]],"date-time":"2024-05-29T21:08:23Z","timestamp":1717016903000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-023-04104-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,12]]},"references-count":29,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,6]]}},"alternative-id":["4104"],"URL":"https:\/\/doi.org\/10.1007\/s10586-023-04104-9","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"type":"print","value":"1386-7857"},{"type":"electronic","value":"1573-7543"}],"subject":[],"published":{"date-parts":[[2023,8,12]]},"assertion":[{"value":"27 December 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 June 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 July 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 August 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}