{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T15:54:38Z","timestamp":1743090878852,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031061554"},{"type":"electronic","value":"9783031061561"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-06156-1_14","type":"book-chapter","created":{"date-parts":[[2022,6,8]],"date-time":"2022-06-08T20:29:39Z","timestamp":1654720179000},"page":"166-178","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Novel Algorithm for Bi-objective Performance-Energy Optimization of Applications with Continuous Performance and Linear Energy Profiles on Heterogeneous HPC Platforms"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4070-7468","authenticated-orcid":false,"given":"Hamidreza","family":"Khaleghzadeh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9181-3290","authenticated-orcid":false,"given":"Ravi Reddy","family":"Manumachu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9460-3897","authenticated-orcid":false,"given":"Alexey","family":"Lastovetsky","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,9]]},"reference":[{"key":"14_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1007\/978-3-319-75178-8_29","volume-title":"Euro-Par 2017: Parallel Processing Workshops","author":"M Ait Aba","year":"2018","unstructured":"Ait Aba, M., Zaourar, L., Munier, A.: Approximation algorithm for scheduling a chain of tasks on heterogeneous systems. In: Heras, D.B., Boug\u00e9, L. (eds.) Euro-Par 2017. LNCS, vol. 10659, pp. 353\u2013365. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-75178-8_29"},{"doi-asserted-by":"crossref","unstructured":"Chakrabarti, A., Parthasarathy, S., Stewart, C.: A pareto framework for data analytics on heterogeneous systems: implications for green energy usage and performance. In: 2017 46th International Conference on Parallel Processing (ICPP), pp. 533\u2013542. IEEE (2017)","key":"14_CR2","DOI":"10.1109\/ICPP.2017.62"},{"key":"14_CR3","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/j.future.2013.07.005","volume":"36","author":"JJ Durillo","year":"2014","unstructured":"Durillo, J.J., Nae, V., Prodan, R.: Multi-objective energy-efficient workflow scheduling using list-based heuristics. Futur. Gener. Comput. Syst. 36, 221\u2013236 (2014)","journal-title":"Futur. Gener. Comput. Syst."},{"unstructured":"Fahad, M., Manumachu, R.R.: HCLWattsUp: energy API using system-level physical power measurements provided by power meters. Heterogeneous Computing Laboratory, University College Dublin, April 2021. https:\/\/csgitlab.ucd.ie\/manumachu\/hclwattsup","key":"14_CR4"},{"doi-asserted-by":"crossref","unstructured":"Fard, H.M., Prodan, R., Barrionuevo, J.J.D., Fahringer, T.: A multi-objective approach for workflow scheduling in heterogeneous environments. In: Proceedings of the 2012 12th IEEE\/ACM International Symposium on Cluster, Cloud and Grid Computing (Ccgrid 2012), CCGRID 2012, pp. 300\u2013309. IEEE Computer Society (2012)","key":"14_CR5","DOI":"10.1109\/CCGrid.2012.114"},{"doi-asserted-by":"crossref","unstructured":"Gholkar, N., Mueller, F., Rountree, B.: Power tuning HPC jobs on power-constrained systems. In: Proceedings of the 2016 International Conference on Parallel Architectures and Compilation, pp. 179\u2013191. ACM (2016)","key":"14_CR6","DOI":"10.1145\/2967938.2967961"},{"issue":"3","key":"14_CR7","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1007\/s10586-012-0210-2","volume":"16","author":"Y Kessaci","year":"2013","unstructured":"Kessaci, Y., Melab, N., Talbi, E.G.: A pareto-based metaheuristic for scheduling HPC applications on a geographically distributed cloud federation. Clust. Comput. 16(3), 451\u2013468 (2013)","journal-title":"Clust. Comput."},{"issue":"3","key":"14_CR8","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1109\/TPDS.2020.3027338","volume":"32","author":"H Khaleghzadeh","year":"2021","unstructured":"Khaleghzadeh, H., Fahad, M., Shahid, A., Manumachu, R.R., Lastovetsky, A.: Bi-objective optimization of data-parallel applications on heterogeneous HPC platforms for performance and energy through workload distribution. IEEE Trans. Parallel Distrib. Syst. 32(3), 543\u2013560 (2021)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"issue":"21","key":"14_CR9","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.5928","volume":"32","author":"H Khaleghzadeh","year":"2020","unstructured":"Khaleghzadeh, H., Fahad, M., Reddy Manumachu, R., Lastovetsky, A.: A novel data partitioning algorithm for dynamic energy optimization on heterogeneous high-performance computing platforms. Concurr. Comput.: Pract. Exper. 32(21), e5928 (2020)","journal-title":"Concurr. Comput.: Pract. Exper."},{"issue":"4","key":"14_CR10","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1002\/cpe.2839","volume":"27","author":"J Ko\u0142odziej","year":"2015","unstructured":"Ko\u0142odziej, J., Khan, S.U., Wang, L., Zomaya, A.Y.: Energy efficient genetic-based schedulers in computational grids. Concurr. Comput.: Pract. Exper. 27(4), 809\u2013829 (2015)","journal-title":"Concurr. Comput.: Pract. Exper."},{"issue":"9","key":"14_CR11","doi-asserted-by":"publisher","first-page":"2884","DOI":"10.1016\/j.jpdc.2014.06.001","volume":"74","author":"J Lang","year":"2014","unstructured":"Lang, J., R\u00fcnger, G.: An execution time and energy model for an energy-aware execution of a conjugate gradient method with CPU\/GPU collaboration. J. Parallel Distrib. Comput. 74(9), 2884\u20132897 (2014)","journal-title":"J. Parallel Distrib. Comput."},{"doi-asserted-by":"crossref","unstructured":"Lastovetsky, A., Reddy, R.: Data partitioning with a realistic performance model of networks of heterogeneous computers. In: 2004 Proceedings of 18th International Parallel and Distributed Processing Symposium, p. 104 (2004)","key":"14_CR12","DOI":"10.1109\/IPDPS.2004.1303051"},{"key":"14_CR13","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1177\/1094342006074864","volume":"21","author":"A Lastovetsky","year":"2007","unstructured":"Lastovetsky, A., Reddy, R.: Data partitioning with a functional performance model of heterogeneous processors. Int. J. High Perform. Comput. Appl. 21, 76\u201390 (2007)","journal-title":"Int. J. High Perform. Comput. Appl."},{"issue":"4","key":"14_CR14","doi-asserted-by":"publisher","first-page":"1119","DOI":"10.1109\/TPDS.2016.2608824","volume":"28","author":"A Lastovetsky","year":"2017","unstructured":"Lastovetsky, A., Reddy, R.: New model-based methods and algorithms for performance and energy optimization of data parallel applications on homogeneous multicore clusters. IEEE Trans. Parallel Distrib. Syst. 28(4), 1119\u20131133 (2017)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"issue":"2","key":"14_CR15","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1109\/TC.2017.2742513","volume":"67","author":"RR Manumachu","year":"2018","unstructured":"Manumachu, R.R., Lastovetsky, A.: Bi-objective optimization of data-parallel applications on homogeneous multicore clusters for performance and energy. IEEE Trans. Comput. 67(2), 160\u2013177 (2018)","journal-title":"IEEE Trans. Comput."},{"doi-asserted-by":"crossref","unstructured":"Miettinen, K.: Nonlinear Multiobjective Optimization. Kluwer (1999)","key":"14_CR16","DOI":"10.1007\/978-1-4615-5563-6"},{"issue":"4","key":"14_CR17","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.4958","volume":"31","author":"R Reddy Manumachu","year":"2019","unstructured":"Reddy Manumachu, R., Lastovetsky, A.L.: Design of self-adaptable data parallel applications on multicore clusters automatically optimized for performance and energy through load distribution. Concurr. Comput.: Pract. Exper. 31(4), e4958 (2019)","journal-title":"Concurr. Comput.: Pract. Exper."},{"key":"14_CR18","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.jnca.2016.10.024","volume":"78","author":"FD Rossi","year":"2017","unstructured":"Rossi, F.D., Xavier, M.G., De Rose, C.A., Calheiros, R.N., Buyya, R.: E-eco: performance-aware energy-efficient cloud data center orchestration. J. Netw. Comput. Appl. 78, 83\u201396 (2017)","journal-title":"J. Netw. Comput. Appl."},{"doi-asserted-by":"crossref","unstructured":"Rountree, B., Lowenthal, D.K., Funk, S., Freeh, V.W., de Supinski, B.R., Schulz, M.: Bounding energy consumption in large-scale MPI programs. In: SC 2007: Proceedings of the 2007 ACM\/IEEE Conference on Supercomputing, pp. 1\u20139 (2007)","key":"14_CR19","DOI":"10.1145\/1362622.1362688"},{"key":"14_CR20","doi-asserted-by":"publisher","DOI":"10.1002\/9780470496916","volume-title":"Metaheuristics: from Design to Implementation","author":"EG Talbi","year":"2009","unstructured":"Talbi, E.G.: Metaheuristics: from Design to Implementation, vol. 74. Wiley, Hoboken (2009)"},{"issue":"6","key":"14_CR21","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.1109\/TPDS.2015.2456020","volume":"27","author":"KM Tarplee","year":"2016","unstructured":"Tarplee, K.M., Friese, R., Maciejewski, A.A., Siegel, H.J., Chong, E.K.: Energy and makespan tradeoffs in heterogeneous computing systems using efficient linear programming techniques. IEEE Trans. Parallel Distrib. Syst. 27(6), 1633\u20131646 (2016)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"14_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jpdc.2015.06.006","volume":"84","author":"L Yu","year":"2015","unstructured":"Yu, L., Zhou, Z., Wallace, S., Papka, M.E., Lan, Z.: Quantitative modeling of power performance tradeoffs on extreme scale systems. J. Parallel Distrib. Comput. 84, 1\u201314 (2015)","journal-title":"J. Parallel Distrib. Comput."}],"container-title":["Lecture Notes in Computer Science","Euro-Par 2021: Parallel Processing Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-06156-1_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T17:41:58Z","timestamp":1727372518000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-06156-1_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031061554","9783031061561"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-06156-1_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"9 June 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Euro-Par","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Parallel Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lisbon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 August 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 August 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"europar2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2021.euro-par.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"136","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"29% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}