{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T16:06:49Z","timestamp":1762272409302,"version":"3.37.3"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2019,6,5]],"date-time":"2019-06-05T00:00:00Z","timestamp":1559692800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,6,5]],"date-time":"2019-06-05T00:00:00Z","timestamp":1559692800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2019,7]]},"DOI":"10.1007\/s11227-019-02908-4","type":"journal-article","created":{"date-parts":[[2019,6,5]],"date-time":"2019-06-05T13:02:34Z","timestamp":1559739754000},"page":"3397-3425","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Time-energy analysis of multilevel parallelism in heterogeneous clusters: the case of EEG classification in BCI tasks"],"prefix":"10.1007","volume":"75","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4258-0264","authenticated-orcid":false,"given":"Juan Jos\u00e9","family":"Escobar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julio","family":"Ortega","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio F.","family":"D\u00edaz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jes\u00fas","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel","family":"Damas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,6,5]]},"reference":[{"issue":"3","key":"2908_CR1","doi-asserted-by":"publisher","first-page":"37:1","DOI":"10.1145\/3078811","volume":"50","author":"K O\u2019brien","year":"2017","unstructured":"O\u2019brien K, Pietri I, Reddy R, Lastovetsky A, Sakellariou R (2017) A survey of power and energy predictive models in HPC systems and applications. ACM Comput Surv 50(3):37:1\u201337:38","journal-title":"ACM Comput Surv"},{"key":"2908_CR2","doi-asserted-by":"crossref","unstructured":"Zhang Y, Hu X. Chen D (2002) Task scheduling and voltage selection for energy minimization. In: Proceedings of the 39th Annual Design Automation Conference. DAC\u20192002, ACM, New Orleans, Louisiana, USA, pp 183\u2013188","DOI":"10.1145\/513918.513966"},{"issue":"4","key":"2908_CR3","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1007\/s10586-009-0119-6","volume":"13","author":"S Baskiyar","year":"2010","unstructured":"Baskiyar S, Abdel-Kader R (2010) Energy aware dag scheduling on heterogeneous systems. Clust Comput 13(4):373\u2013383","journal-title":"Clust Comput"},{"issue":"8","key":"2908_CR4","doi-asserted-by":"publisher","first-page":"1374","DOI":"10.1109\/TPDS.2010.208","volume":"22","author":"Y Lee","year":"2011","unstructured":"Lee Y, Zomaya A (2011) Energy conscious scheduling for distributed computing systems under different operating conditions. IEEE Trans Parallel Distrib Syst 22(8):1374\u20131381","journal-title":"IEEE Trans Parallel Distrib Syst"},{"issue":"4","key":"2908_CR5","first-page":"252","volume":"4","author":"B Dorronsoro","year":"2014","unstructured":"Dorronsoro B, Nesmachnow S, Taheri J, Zomaya A, Talbi EG, Bouvry P (2014) A hierarchical approach for energy-efficient scheduling of large workloads in multicore distributed systems. Sustain Comput Inform Syst 4(4):252\u2013261","journal-title":"Sustain Comput Inform Syst"},{"key":"2908_CR6","doi-asserted-by":"crossref","unstructured":"Barik R, Farooqui N, Lewis B, Hu C, Shpeisman T (2016) A black-box approach to energy-aware scheduling on integrated CPU\u2013GPU systems. In: Proceedings of the 2016 International Symposium on Code Generation and Optimization. CGO\u20192016, ACM, Barcelona, Spain, pp 70\u201381","DOI":"10.1145\/2854038.2854052"},{"issue":"1","key":"2908_CR7","first-page":"149","volume":"15","author":"J Ortega","year":"2016","unstructured":"Ortega J, Asensio-Cubero J, Gan J, Ortiz A (2016) Classification of motor imagery tasks for BCI with multiresolution analysis and multiobjective feature selection. BioMed Eng OnLine 15(1):149\u2013164","journal-title":"BioMed Eng OnLine"},{"key":"2908_CR8","first-page":"72","volume":"19","author":"K Raju","year":"2018","unstructured":"Raju K, Niranjan N (2018) A survey on techniques for cooperative CPU\u2013GPU computing. Sustain Comput Inform Syst 19:72\u201385","journal-title":"Sustain Comput Inform Syst"},{"issue":"2","key":"2908_CR9","doi-asserted-by":"publisher","first-page":"19:1","DOI":"10.1145\/2636342","volume":"47","author":"S Mittal","year":"2014","unstructured":"Mittal S, Vetter J (2014) A survey of methods for analyzing and improving GPU energy efficiency. ACM Comput Surv 47(2):19:1\u201319:23","journal-title":"ACM Comput Surv"},{"key":"2908_CR10","doi-asserted-by":"crossref","unstructured":"Escobar J, Ortega J, D\u00edaz A, Gonz\u00e1lez J, Damas M (2018) Speedup and energy analysis of EEG classification for BCI tasks on CPU\u2013GPU clusters. In: Proceedings of the 6th International Workshop on Parallelism in Bioinformatics. PBIO\u20192018, ACM, Barcelona, Spain, pp 33\u201343","DOI":"10.1145\/3235830.3235834"},{"issue":"12","key":"2908_CR11","doi-asserted-by":"publisher","first-page":"3227","DOI":"10.1007\/s00500-015-2005-x","volume":"21","author":"P Vidal","year":"2017","unstructured":"Vidal P, Alba E, Luna F (2017) Solving optimization problems using a hybrid systolic search on GPU plus CPU. Soft Comput 21(12):3227\u20133245","journal-title":"Soft Comput"},{"key":"2908_CR12","doi-asserted-by":"crossref","unstructured":"Luong T, Melab N, Talbi E.G (July 2010) gPU-based island model for evolutionary algorithms. In: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation. GECCO\u20192010, ACM, Portland, OR, USA, pp 1089\u20131096","DOI":"10.1145\/1830483.1830685"},{"key":"2908_CR13","doi-asserted-by":"crossref","unstructured":"Pospichal P, Jaros J, Schwarz J (2010) Parallel genetic algorithm on the cuda architecture. In: Proceedings of the 13th European Conference on the Applications of Evolutionary Computation. EvoApplications\u20192010, Springer, Istambul, Turkey, pp 442\u2013451","DOI":"10.1007\/978-3-642-12239-2_46"},{"key":"2908_CR14","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/978-3-642-37959-8_13","volume-title":"Massively parallel evolutionary computation on GPGPUs. Natural computing series","author":"D Sharma","year":"2013","unstructured":"Sharma D, Collet P (2013) Implementation techniques for massively parallel multi-objective optimization. In: Tsutsui S, Collet P (eds) Massively parallel evolutionary computation on GPGPUs. Natural computing series. Springer, Berlin, pp 267\u2013286"},{"key":"2908_CR15","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1007\/978-3-642-37959-8_14","volume-title":"Massively parallel evolutionary computation on GPGPUs. Natural computing series","author":"M Wong","year":"2013","unstructured":"Wong M, Cui G (2013) Data mining using parallel multi-objective evolutionary algorithms on graphics processing units. In: Tsutsui S, Collet P (eds) Massively parallel evolutionary computation on GPGPUs. Natural computing series. Springer, Berlin, pp 287\u2013307"},{"key":"2908_CR16","doi-asserted-by":"crossref","unstructured":"Gainaru A, Slusanschi E, Trausan-Matu S (2011) Mapping data mining algorithms on a gpu architecture: a study. In: Proceedings of the 19th International Symposium. Foundations of Intelligent Systems. ISMIS\u20192011, Springer, Warsaw, Poland, pp 102\u2013112","DOI":"10.1007\/978-3-642-21916-0_12"},{"key":"2908_CR17","doi-asserted-by":"crossref","unstructured":"Coello Coello C, Sierra M (2004) A study of the parallelization of a coevolutionary multi-objective evolutionary algorithm. In: Proceedings of the 3rd Mexican International Conference on Artificial Intelligence. MICAI\u20192004, Springer, Mexico City, Mexico, pp 688\u2013697","DOI":"10.1007\/978-3-540-24694-7_71"},{"issue":"1","key":"2908_CR18","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/s00224-007-9070-1","volume":"43","author":"K Pruhs","year":"2008","unstructured":"Pruhs K, Stee R, Uthaisombut P (2008) Speed scaling of tasks with precedence constraints. Theory Comput Syst 43(1):67\u201380","journal-title":"Theory Comput Syst"},{"issue":"10","key":"2908_CR19","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1109\/MC.2016.309","volume":"49","author":"E Rotem","year":"2016","unstructured":"Rotem E, Weiser U, Mendelson A, Ginosar R, Weissmann E, Aizik Y (2016) H-earth: heterogeneous multicore platform energy management. IEEE Comput Mag 49(10):47\u201355","journal-title":"IEEE Comput Mag"},{"issue":"4","key":"2908_CR20","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1007\/s10723-013-9258-3","volume":"11","author":"S Nesmachnow","year":"2013","unstructured":"Nesmachnow S, Dorronsoro B, Pecero J, Bouvry P (2013) Energy-aware scheduling on multicore heterogeneous grid computing systems. J Grid Comput 11(4):653\u2013680","journal-title":"J Grid Comput"},{"issue":"1","key":"2908_CR21","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10586-011-0171-x","volume":"16","author":"G Valentini","year":"2013","unstructured":"Valentini G, Lassonde W, Khan S, Min-Allah N, Madani S, Li J, Zhang L, Wang L, Ghani N, Kolodziej J, Li H, Zomaya A, Xu CZ, Balaji P, Vishnu A, Pinel F, Pecero J, Kliazovich D, Bouvry P (2013) An overview of energy efficiency techniques in cluster computing systems. Clust Comput 16(1):3\u201315","journal-title":"Clust Comput"},{"issue":"3","key":"2908_CR22","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1145\/1816038.1815998","volume":"38","author":"S Hong","year":"2010","unstructured":"Hong S, Kim H (2010) An integrated GPU power and performance model. SIGARCH Comput Arch News 38(3):280\u2013289","journal-title":"SIGARCH Comput Arch News"},{"key":"2908_CR23","doi-asserted-by":"crossref","unstructured":"Ge R, Feng X, Burtscher M, Zong Z (2014) Peach: a model for performance and energy aware cooperative hybrid computing. In: Proceedings of the 11th ACM Conference on Computing Frontiers. CF\u20192014, ACM, Cagliari, Italy, pp 24:1\u201324:2","DOI":"10.1145\/2597917.2597948"},{"key":"2908_CR24","doi-asserted-by":"crossref","unstructured":"De Sensi D (2016) Predicting performance and power consumption of parallel applications. In: Proceedings of the 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing. PDP\u20192016, IEEE, Heraklion Crete, Greece, pp 200\u2013207","DOI":"10.1109\/PDP.2016.41"},{"key":"2908_CR25","doi-asserted-by":"crossref","unstructured":"Marowka A (2012) Energy consumption modeling for hybrid computing. In: Proceedings of the 18th International Conference on Parallel Processing, Euro-Par 2012. Euro-Par\u20192012, Springer, Rhodes Island, Greece, pp 54\u201364","DOI":"10.1007\/978-3-642-32820-6_8"},{"key":"2908_CR26","doi-asserted-by":"crossref","unstructured":"Ma K, Li X, Chen W, Zhang C, Wang X (2012) Greengpu: a holistic approach to energy efficiency in GPU\u2013CPU heterogeneous architectures. In: Proceedings of the 41st International Conference on Parallel Processing. ICPP\u20192012, IEEE, Pittsburgh, PA, USA, pp 48\u201357","DOI":"10.1109\/ICPP.2012.31"},{"key":"2908_CR27","doi-asserted-by":"crossref","unstructured":"Allen T, Ge R (2016) Characterizing power and performance of GPU memory access. In: Proceedings of the 4th International Workshop on Energy Efficient Supercomputing. E2SC\u20192016, IEEE Press, Salt Lake City, Utah, USA, pp 46\u201353","DOI":"10.1109\/E2SC.2016.012"},{"key":"2908_CR28","unstructured":"Escobar J, Ortega J, D\u00edaz A, Gonz\u00e1lez J, Damas M (2018) Energy-aware load balancing of parallel evolutionary algorithms with heavy fitness functions in heterogeneous CPU\u2013GPU architectures. Concurrency and Computation: Practice and Experience, p e4688"},{"key":"2908_CR29","unstructured":"Free Software Foundation: GNU gprof documentation. \n                    https:\/\/ftp.gnu.org\/pub\/old-gnu\/Manuals\/gprof-2.9.1\/html_node\/gprof_toc.html\n                    \n                  . Accessed 10 Feb 2017"},{"key":"2908_CR30","first-page":"1157","volume":"3","author":"I Guyon","year":"2003","unstructured":"Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157\u20131182","journal-title":"J Mach Learn Res"},{"key":"2908_CR31","doi-asserted-by":"crossref","unstructured":"Charikar M, Guruswami V, Kumar R, Rajagopalan S, Sahai A (2000) Combinatorial feature selection problems. In: Proceedings of the 41st Annual Symposium on Foundations of Computer Science. FOCS\u20192000, IEEE, Redondo Beach, CA, USA, pp 631\u2013640","DOI":"10.1109\/SFCS.2000.892331"},{"key":"2908_CR32","unstructured":"Khronos Group: Khronos opencl registry (2015). \n                    https:\/\/www.khronos.org\/registry\/cl\/\n                    \n                  . Accessed 30 Nov 2015"},{"key":"2908_CR33","unstructured":"OpenMP Community: Openmp specifications. \n                    http:\/\/www.openmp.org\/specifications\/\n                    \n                  . Accessed 21 Nov 2016"},{"key":"2908_CR34","doi-asserted-by":"crossref","unstructured":"Escobar J, Ortega J, D\u00edaz A, Gonz\u00e1lez J, Damas M (2018) Multi-objective feature selection for eeg classification with multi-level parallelism on heterogeneous CPU\u2013GPU clusters. In: Proceedings of the Annual Conference on Genetic and Evolutionary Computation. GECCO\u20192018, ACM, Kyoto, Japan, pp 1862\u20131869","DOI":"10.1145\/3205651.3208239"},{"key":"2908_CR35","unstructured":"The Open MPI Project: Openmpi documentation. \n                    https:\/\/www.open-mpi.org\/doc\/\n                    \n                  . Accessed 19 Nov 2018"},{"key":"2908_CR36","doi-asserted-by":"crossref","unstructured":"Escobar J, Ortega J, Gonz\u00e1lez J, Damas M (2016) Assessing parallel heterogeneous computer architectures for multiobjective feature selection on EEG classification. In: Proceedings of the 4th International Conference on Bioinformatics and Biomedical Engineering. IWBBIO\u20192016, Springer, Granada, Spain, pp 277\u2013289","DOI":"10.1007\/978-3-319-31744-1_25"},{"key":"2908_CR37","unstructured":"Escobar J, Ortega J, Gonz\u00e1lez J, Damas M (2016) Improving memory accesses for heterogeneous parallel multi-objective feature selection on EEG classification. In: Proceedings of the 4th International Workshop on Parallelism in Bioinformatics. PBIO\u20192016, Springer, Grenoble, France, pp 372\u2013383"},{"issue":"3","key":"2908_CR38","doi-asserted-by":"publisher","first-page":"1881","DOI":"10.1007\/s10586-017-0980-7","volume":"20","author":"J Escobar","year":"2017","unstructured":"Escobar J, Ortega J, Gonz\u00e1lez J, Damas M, D\u00edaz A (2017) Parallel high-dimensional multi-objective feature selection for EEG classification with dynamic workload balancing on CPU\u2013GPU. Clust Comput 20(3):1881\u20131897","journal-title":"Clust Comput"},{"issue":"4","key":"2908_CR39","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1088\/1741-2560\/10\/4\/046014","volume":"10","author":"J Asensio-Cubero","year":"2013","unstructured":"Asensio-Cubero J, Gan J, Palaniappan R (2013) Multiresolution analysis over simple graphs for brain computer interfaces. J Neural Eng 10(4):21\u201326","journal-title":"J Neural Eng"},{"key":"2908_CR40","doi-asserted-by":"crossref","unstructured":"Zitzler E, Thiele L (1998) Multiobjective optimization using evolutionary algorithms\u2014a comparative case study. In: Proceedings of the 5th International Conference on Parallel Problem Solving from Nature. PPSN V, Springer, Amsterdam, The Netherlands, pp 292\u2013301","DOI":"10.1007\/BFb0056872"},{"key":"2908_CR41","volume-title":"Evolutionary algorithms for multiobjective optimization: methods and applications","author":"E Zitzler","year":"1999","unstructured":"Zitzler E (1999) Evolutionary algorithms for multiobjective optimization: methods and applications. Shaker Verlag, Herzogenrath"},{"key":"2908_CR42","doi-asserted-by":"crossref","unstructured":"S\u00eerbu A, Babaoglu O (2016) Power consumption modeling and prediction in a hybrid CPU\u2013GPU\u2013MIC supercomputer. In: Proceedings of the 22nd International Conference on Parallel Processing, Euro-Par 2016. Euro-Par\u20192016, Springer, Grenoble, France, pp 117\u2013130","DOI":"10.1007\/978-3-319-43659-3_9"},{"key":"2908_CR43","unstructured":"Advanced Configuration and Power Interface (ACPI): Acpi specification. \n                    http:\/\/www.acpi.info\/spec.htm\n                    \n                  . Accessed 30 Nov 2018"},{"key":"2908_CR44","unstructured":"CPUFreq Governors: information for users and developers. \n                    https:\/\/www.kernel.org\/doc\/Documentation\/cpu-freq\/governors.txt\n                    \n                  . Accessed 30 Nov 2018"},{"key":"2908_CR45","unstructured":"Mathworks: Matlab histfit function. \n                    https:\/\/mathworks.com\/help\/stats\/histfit.html\n                    \n                  . Accessed 02 Dec 2018"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-019-02908-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11227-019-02908-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-019-02908-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T23:11:16Z","timestamp":1591225876000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11227-019-02908-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,5]]},"references-count":45,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2019,7]]}},"alternative-id":["2908"],"URL":"https:\/\/doi.org\/10.1007\/s11227-019-02908-4","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"type":"print","value":"0920-8542"},{"type":"electronic","value":"1573-0484"}],"subject":[],"published":{"date-parts":[[2019,6,5]]},"assertion":[{"value":"5 June 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}