{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:40:19Z","timestamp":1740123619350,"version":"3.37.3"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2020,8,18]],"date-time":"2020-08-18T00:00:00Z","timestamp":1597708800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,8,18]],"date-time":"2020-08-18T00:00:00Z","timestamp":1597708800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1007\/s11227-020-03400-0","type":"journal-article","created":{"date-parts":[[2020,8,18]],"date-time":"2020-08-18T14:02:47Z","timestamp":1597759367000},"page":"3381-3401","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SMOaaS: a Scalable Matrix Operation as a Service model in Cloud"],"prefix":"10.1007","volume":"77","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5721-5534","authenticated-orcid":false,"given":"KC","family":"Ujjwal","sequence":"first","affiliation":[]},{"given":"Sudheer Kumar","family":"Battula","sequence":"additional","affiliation":[]},{"given":"Saurabh","family":"Garg","sequence":"additional","affiliation":[]},{"given":"Ranesh Kumar","family":"Naha","sequence":"additional","affiliation":[]},{"given":"Md Anwarul Kaium","family":"Patwary","sequence":"additional","affiliation":[]},{"given":"Alexander","family":"Brown","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,8,18]]},"reference":[{"issue":"4","key":"3400_CR1","doi-asserted-by":"publisher","first-page":"619","DOI":"10.21136\/CMJ.1975.101357","volume":"25","author":"M Fiedler","year":"1975","unstructured":"Fiedler M (1975) A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory. Czech Math J 25(4):619\u2013633","journal-title":"Czech Math J"},{"key":"3400_CR2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9780898719048","volume-title":"Generalized inverses of linear transformations","author":"SL Campbell","year":"2009","unstructured":"Campbell SL, Meyer CD (2009) Generalized inverses of linear transformations. SIAM, Philadelphia"},{"key":"3400_CR3","volume-title":"Probability and computing: randomization and probabilistic techniques in algorithms and data analysis","author":"M Mitzenmacher","year":"2017","unstructured":"Mitzenmacher M, Upfal E (2017) Probability and computing: randomization and probabilistic techniques in algorithms and data analysis. Cambridge University Press, Cambridge"},{"key":"3400_CR4","unstructured":"Krishnan M, Nieplocha J (2004) SRUMMA: a matrix multiplication algorithm suitable for clusters and scalable shared memory systems. In: 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings, p\u00a070. IEEE"},{"issue":"1","key":"3400_CR5","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1145\/1327452.1327492","volume":"51","author":"J Dean","year":"2008","unstructured":"Dean J, Ghemawat S (2008) Mapreduce: simplified data processing on large clusters. Commun ACM 51(1):107\u2013113","journal-title":"Commun ACM"},{"key":"3400_CR6","doi-asserted-by":"crossref","unstructured":"Gittens A, Devarakonda A, Racah E, Ringenburg M, Gerhardt L, Kottalam J, Liu J, Maschhoff K, Canon S, Chhugani J et al (2016) Matrix factorizations at scale: a comparison of scientific data analytics in spark and C+ MPI using three case studies. In: 2016 IEEE International Conference on Big Data (Big Data). IEEE, pp 204\u2013213","DOI":"10.1109\/BigData.2016.7840606"},{"key":"3400_CR7","doi-asserted-by":"crossref","unstructured":"Gupta V, Wang S, Courtade T, Ramchandran K (2018) Oversketch: approximate matrix multiplication for the cloud. In: 2018 IEEE International Conference on Big Data (Big Data). IEEE, pp 298\u2013304","DOI":"10.1109\/BigData.2018.8622139"},{"issue":"3","key":"3400_CR8","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1007\/s00453-002-0962-9","volume":"34","author":"O Beaumont","year":"2002","unstructured":"Beaumont O, Boudet V, Rastello F, Robert Y et al (2002) Partitioning a square into rectangles: NP-completeness and approximation algorithms. Algorithmica 34(3):217\u2013239","journal-title":"Algorithmica"},{"issue":"12","key":"3400_CR9","doi-asserted-by":"publisher","first-page":"1539","DOI":"10.1016\/j.jpdc.2013.07.017","volume":"73","author":"JC Pichel","year":"2013","unstructured":"Pichel JC, Rivera FF (2013) Sparse matrix vector multiplication on the single-chip cloud computer many-core processor. J Parallel Distrib Comput 73(12):1539\u20131550 (Heterogeneity in Parallel and Distributed Computing)","journal-title":"J Parallel Distrib Comput"},{"issue":"4","key":"3400_CR10","doi-asserted-by":"publisher","first-page":"231","DOI":"10.14778\/1938545.1938548","volume":"4","author":"X Yang","year":"2011","unstructured":"Yang X, Parthasarathy S, Sadayappan P (2011) Fast sparse matrix-vector multiplication on GPUs: implications for graph mining. Proc VLDB Endow 4(4):231\u2013242","journal-title":"Proc VLDB Endow"},{"key":"3400_CR11","doi-asserted-by":"crossref","unstructured":"Ashari A, Sedaghati N, Eisenlohr J, Parthasarath S, Sadayappan P (2014) Fast sparse matrix-vector multiplication on GPUs for graph applications. In: SC \u201914:Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp 781\u2013792","DOI":"10.1109\/SC.2014.69"},{"issue":"1","key":"3400_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3232850","volume":"45","author":"W Boukaram","year":"2019","unstructured":"Boukaram W, Turkiyyah G, Keyes D (2019) Hierarchical matrix operations on GPUs: matrix-vector multiplication and compression. ACM Trans Math Softw 45(1):1\u201328","journal-title":"ACM Trans Math Softw"},{"key":"3400_CR13","doi-asserted-by":"crossref","unstructured":"Seo S, Yoon EJ, Kim J, Jin S, Kim J, Maeng S (2010) Hama: an efficient matrix computation with the mapreduce framework. In: 2010 IEEE Second International Conference on Cloud Computing Technology and Science, pp 721\u2013726","DOI":"10.1109\/CloudCom.2010.17"},{"key":"3400_CR14","doi-asserted-by":"crossref","unstructured":"Gu R, Tang Y, Wang Z, Wang S, Yin X, Yuan C, Huang Y (2015) Efficient large scale distributed matrix computation with spark. In: 2015 IEEE International Conference on Big Data (Big Data), pp 2327\u20132336","DOI":"10.1109\/BigData.2015.7364023"},{"key":"3400_CR15","doi-asserted-by":"publisher","first-page":"2166","DOI":"10.1109\/ACCESS.2016.2546544","volume":"4","author":"J Liu","year":"2016","unstructured":"Liu J, Liang Y, Ansari N (2016) Spark-based large-scale matrix inversion for big data processing. IEEE Access 4:2166\u20132176","journal-title":"IEEE Access"},{"key":"3400_CR16","doi-asserted-by":"crossref","unstructured":"DeFlumere A, Lastovetsky A (2014) Searching for the optimal data partitioning shape for parallel matrix matrix multiplication on 3 heterogeneous processors. In: 2014 IEEE International Parallel and Distributed Processing Symposium Workshops. IEEE, pp 17\u201328","DOI":"10.1109\/IPDPSW.2014.8"},{"key":"3400_CR17","doi-asserted-by":"crossref","unstructured":"Dovolnov E, Kalinov A, Klimov S (2003) Natural block data decomposition for heterogeneous clusters. In: Proceedings International Parallel and Distributed Processing Symposium. IEEE, p 10","DOI":"10.1109\/IPDPS.2003.1213209"},{"key":"3400_CR18","doi-asserted-by":"crossref","unstructured":"Lastovetsky Alexey (2007) On grid-based matrix partitioning for heterogeneous processors. In: Sixth International Symposium on Parallel and Distributed Computing (ISPDC\u201907). IEEE, p 51","DOI":"10.1109\/ISPDC.2007.38"},{"key":"3400_CR19","doi-asserted-by":"crossref","unstructured":"Clarke D, Lastovetsky A, Rychkov V (2012) Column-based matrix partitioning for parallel matrix multiplication on heterogeneous processors based on functional performance models. In: Euro-Par 2011: Parallel Processing Workshops. Springer, Berlin, pp 450\u2013459","DOI":"10.1007\/978-3-642-29737-3_50"},{"issue":"3","key":"3400_CR20","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1002\/cpe.3609","volume":"28","author":"T Malik","year":"2016","unstructured":"Malik T, Rychkov V, Lastovetsky A (2016) Network-aware optimization of communications for parallel matrix multiplication on hierarchical hpc platforms. Concurr Comput Pract Exp 28(3):802\u2013821","journal-title":"Concurr Comput Pract Exp"},{"key":"3400_CR21","doi-asserted-by":"crossref","unstructured":"Wang S, Huang J, Lee W, Lee K (2018) Scaling up matrix factorization with cloud computing for collaborative recommendation. In: 2018 International Conference on System Science and Engineering (ICSSE), pp 1\u20136","DOI":"10.1109\/ICSSE.2018.8520095"},{"key":"3400_CR22","doi-asserted-by":"crossref","unstructured":"Gupta V, Wang S, Courtade T, Ramchandran K (2018) Oversketch: approximate matrix multiplication for the cloud. pp 298\u2013304","DOI":"10.1109\/BigData.2018.8622139"},{"key":"3400_CR23","doi-asserted-by":"crossref","unstructured":"Qian Z, Chen X, Kang N, Chen M, Yu Y, Moscibroda T, Zhang Z (2012) Madlinq: large-scale distributed matrix computation for the cloud. In: Proceedings of the 7th ACM European Conference on Computer Systems, EuroSys 12, New York, NY, USA. Association for Computing Machinery, p 197210","DOI":"10.1145\/2168836.2168857"},{"issue":"1","key":"3400_CR24","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1109\/TPDS.2018.2853151","volume":"30","author":"O Beaumont","year":"2019","unstructured":"Beaumont O, Becker BA, DeFlumere A, Eyraud-Dubois L, Lambert T, Lastovetsky A (2019) Recent advances in matrix partitioning for parallel computing on heterogeneous platforms. IEEE Trans Parallel Distrib Syst 30(1):218\u2013229","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"3400_CR25","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/j.ins.2020.03.020","volume":"523","author":"Y Chen","year":"2020","unstructured":"Chen Y, Xiao G, Fan W, Tang Z, Li K (2020) tpSpMV: a two-phase large-scale sparse matrix-vector multiplication kernel for manycore architectures. Inf Sci 523:279\u2013295","journal-title":"Inf Sci"},{"issue":"1","key":"3400_CR26","doi-asserted-by":"publisher","first-page":"74","DOI":"10.3390\/rs10010074","volume":"10","author":"S Garg","year":"2018","unstructured":"Garg S, Forbes-Smith N, Hilton J, Prakash M (2018) SparkCloud: a cloud-based elastic bushfire simulation service. Remote Sens 10(1):74","journal-title":"Remote Sens"},{"key":"3400_CR27","unstructured":"Nectar Cloud (2019) https:\/\/nectar.org.au\/research-cloud\/. Accessed 12 May 2018"},{"key":"3400_CR28","unstructured":"Jeremy Unruh (2019) Openstack4j. http:\/\/www.openstack4j.com\/. Accessed 20 Feb 2019"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-020-03400-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-020-03400-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-020-03400-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T23:51:54Z","timestamp":1629244314000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-020-03400-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,18]]},"references-count":28,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,4]]}},"alternative-id":["3400"],"URL":"https:\/\/doi.org\/10.1007\/s11227-020-03400-0","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"type":"print","value":"0920-8542"},{"type":"electronic","value":"1573-0484"}],"subject":[],"published":{"date-parts":[[2020,8,18]]},"assertion":[{"value":"18 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}