{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:44:48Z","timestamp":1742913888814,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031683084"},{"type":"electronic","value":"9783031683091"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-68309-1_15","type":"book-chapter","created":{"date-parts":[[2024,8,17]],"date-time":"2024-08-17T14:02:25Z","timestamp":1723903345000},"page":"179-193","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Chorus: More Efficient Machine Learning on Serverless Platform"],"prefix":"10.1007","author":[{"given":"Guang","family":"Yang","sequence":"first","affiliation":[]},{"given":"Jie","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Shuai","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Muzi","family":"Qu","sequence":"additional","affiliation":[]},{"given":"Dan","family":"Ye","sequence":"additional","affiliation":[]},{"given":"Hua","family":"Zhong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,8,18]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Jonas, E., Pu, Q., Venkataraman, S., Stoica, I., Recht, B.: Occupy the cloud: distributed computing for the 99%. In: Proceedings of the 2017 Symposium on Cloud Computing, pp. 445\u2013451 (2017)","DOI":"10.1145\/3127479.3128601"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Carver, B., Zhang, J., Wang, A., Cheng, Y.: In search of a fast and efficient serverless dag engine. In: 2019 IEEE\/ACM Fourth International Parallel Data Systems Workshop (PDSW), pp. 1\u201310. IEEE (2019)","DOI":"10.1109\/PDSW49588.2019.00005"},{"key":"15_CR3","unstructured":"Shankar, V., et al.: Numpywren: serverless linear algebra. arXiv preprint arXiv:1810.09679 (2018)"},{"key":"15_CR4","unstructured":"Fouladi, S., et al.: Encoding, fast and slow: low-latency video processing using thousands of tiny threads. In: NSDI, vol. 17, pp. 363\u2013376 (2017)"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Ao, L., Izhikevich, L., Voelker, G.M., Porter, G.: Sprocket: a serverless video processing framework. In: Proceedings of the ACM Symposium on Cloud Computing, pp. 263\u2013274 (2018)","DOI":"10.1145\/3267809.3267815"},{"key":"15_CR6","unstructured":"Fouladi, S., Romero, F., Iter, D., Li, Q., Chatterjee, S.: From laptop to lambda: outsourcing everyday jobs to thousands of transient functional containers. In: 2019 USENIX Annual Technical Conference (USENIX ATC 2019), p. 14 (2019)"},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"Li, M., et al.: Scaling distributed machine learning with the parameter server. In: 11th USENIX Symposium on Operating Systems Design and Implementation (OSDI 2014), pp. 583\u2013598 (2014)","DOI":"10.1145\/2640087.2644155"},{"key":"15_CR8","unstructured":"Ho, Q., et al.: More effective distributed ML via a stale synchronous parallel parameter server. In: Advances in Neural Information Processing Systems, vol. 26 (2013)"},{"key":"15_CR9","doi-asserted-by":"crossref","unstructured":"Aytekin, A., Johansson, M.: Harnessing the power of serverless runtimes for large-scale optimization. arXiv:1901.03161 (2019)","DOI":"10.1109\/CLOUD.2019.00090"},{"key":"15_CR10","doi-asserted-by":"crossref","unstructured":"Carreira, J., Fonseca, P., Tumanov, A., Zhang, A., Katz, R.: Cirrus: a serverless framework for end-to-end ML workflows. In: Proceedings of the ACM Symposium on Cloud Computing, pp. 13\u201324 (2019)","DOI":"10.1145\/3357223.3362711"},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Wang, H., Niu, D., Li, B.: Distributed machine learning with a serverless architecture. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pp. 1288\u20131296. IEEE (2019)","DOI":"10.1109\/INFOCOM.2019.8737391"},{"key":"15_CR12","unstructured":"Ali, A., Zawad, S., Aditya, P., Akkus, I.E., Chen, R., Yan, F.: SMLT: a serverless framework for scalable and adaptive machine learning design and training. arXiv:2205.01853 (2022)"},{"key":"15_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2023.104764","volume":"183","author":"P Gimeno Sarroca","year":"2024","unstructured":"Gimeno Sarroca, P., S\u00e1nchez-Artigas, M.: MLLess: achieving cost efficiency in serverless machine learning training. J. Parallel Distrib. Comput. 183, 104764 (2024)","journal-title":"J. Parallel Distrib. Comput."},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Feng, L., Kudva, P., Da Silva, D., Hu, J.: Exploring serverless computing for neural network training. In: 2018 IEEE 11th International Conference on Cloud Computing (CLOUD) (2018)","DOI":"10.1109\/CLOUD.2018.00049"},{"key":"15_CR15","unstructured":"Thorpe, J., et al.: Dorylus: affordable, scalable, and accurate GNN training with distributed CPU servers and serverless threads. In: 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 2021), pp. 495\u2013514 (2021)"},{"key":"15_CR16","unstructured":"Criteo_dataset | Kaggle. https:\/\/www.kaggle.com\/datasets\/mrkmakr\/criteo-dataset. Accessed 1 Apr 2024"},{"key":"15_CR17","unstructured":"Netflix Prize data | Kaggle. https:\/\/www.kaggle.com\/netflix-inc\/netflix-prize-data. Accessed 1 Apr 2024"}],"container-title":["Lecture Notes in Computer Science","Database and Expert Systems Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-68309-1_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,17]],"date-time":"2024-08-17T14:04:19Z","timestamp":1723903459000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-68309-1_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031683084","9783031683091"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-68309-1_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"18 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DEXA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database and Expert Systems Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Naples","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"35","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dexa2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.dexa.org\/dexa2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}