{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T05:35:40Z","timestamp":1743053740344,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031304415"},{"type":"electronic","value":"9783031304422"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-30442-2_25","type":"book-chapter","created":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T10:02:09Z","timestamp":1682589729000},"page":"333-345","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Breaking Down\u00a0the\u00a0Parallel Performance of\u00a0GROMACS, a\u00a0High-Performance Molecular Dynamics Software"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6384-2630","authenticated-orcid":false,"given":"M\u00e5ns I.","family":"Andersson","sequence":"first","affiliation":[]},{"given":"Natarajan Arul","family":"Murugan","sequence":"additional","affiliation":[]},{"given":"Artur","family":"Podobas","sequence":"additional","affiliation":[]},{"given":"Stefano","family":"Markidis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,28]]},"reference":[{"key":"25_CR1","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.softx.2015.06.001","volume":"1","author":"M Abraham","year":"2015","unstructured":"Abraham, M., et al.: GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1, 19\u201325 (2015). https:\/\/doi.org\/10.1016\/j.softx.2015.06.001","journal-title":"SoftwareX"},{"issue":"1\u20133","key":"25_CR2","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/0010-4655(95)00042-E","volume":"91","author":"HJ Berendsen","year":"1995","unstructured":"Berendsen, H.J., van der Spoel, D., van Drunen, R.: GROMACS: a message-passing parallel molecular dynamics implementation. Comput. Phys. Commun. 91(1\u20133), 43\u201356 (1995). https:\/\/doi.org\/10.1016\/0010-4655(95)00042-E","journal-title":"Comput. Phys. Commun."},{"issue":"1","key":"25_CR3","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/s10822-011-9517-y","volume":"26","author":"DW Borhani","year":"2012","unstructured":"Borhani, D.W., Shaw, D.E.: The future of molecular dynamics simulations in drug discovery. J. Comput. Aided Mol. Des. 26(1), 15\u201326 (2012). https:\/\/doi.org\/10.1007\/s10822-011-9517-y","journal-title":"J. Comput. Aided Mol. Des."},{"key":"25_CR4","doi-asserted-by":"publisher","unstructured":"Brooks, B.R., al.: Charmm: the biomolecular simulation program. J. Comput. chem. 30(10), 1545\u20131614 (2009). https:\/\/doi.org\/10.1002\/jcc.21287","DOI":"10.1002\/jcc.21287"},{"issue":"2","key":"25_CR5","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.sbi.2005.02.004","volume":"15","author":"R Elber","year":"2005","unstructured":"Elber, R.: Long-timescale simulation methods. Curr. Opin. Struct. Biol. 15(2), 151\u2013156 (2005). https:\/\/doi.org\/10.1016\/j.sbi.2005.02.004","journal-title":"Curr. Opin. Struct. Biol."},{"key":"25_CR6","doi-asserted-by":"publisher","unstructured":"Frigo, M., Johnson, S.G.: The design and implementation of FFTW3. Proc. IEEE 93(2), 216\u2013231 (2005). https:\/\/doi.org\/10.1109\/JPROC.2004.840301, special issue on \u201cProgram Generation, Optimization, and Platform Adaptation\"","DOI":"10.1109\/JPROC.2004.840301"},{"key":"25_CR7","doi-asserted-by":"publisher","unstructured":"Gruber, C.C., Pleiss, J.: Systematic benchmarking of large molecular dynamics simulations employing GROMACS on massive multiprocessing facilities. J. Comput. Chem. 32(4), 600\u2013606 (2011). https:\/\/doi.org\/10.1002\/jcc.21645","DOI":"10.1002\/jcc.21645"},{"issue":"9","key":"25_CR8","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1038\/nsb0902-646","volume":"9","author":"M Karplus","year":"2002","unstructured":"Karplus, M., McCammon, J.A.: Molecular dynamics simulations of biomolecules. Nat. Struct. Biol. 9(9), 646\u2013652 (2002). https:\/\/doi.org\/10.1038\/nsb0902-646","journal-title":"Nat. Struct. Biol."},{"key":"25_CR9","doi-asserted-by":"publisher","unstructured":"Kn\u00fcpfer, A., et al.: Score-p: a joint performance measurement run-time infrastructure for periscope, scalasca, TAU, and vampir. In: Brunst, H., Muller, M., Nagel, W., Resch, M. (eds.) Tools for High Performance Computing 2011, pp. 79\u201391. Springer, Berlin (2012). https:\/\/doi.org\/10.1007\/978-3-642-31476-6_7","DOI":"10.1007\/978-3-642-31476-6_7"},{"key":"25_CR10","doi-asserted-by":"publisher","unstructured":"Kn\u00fcpfer, A., et al.: The vampir performance analysis tool-set. In: Tools for High Performance Computing, pp. 139\u2013155. Springer, Berlin (2008). https:\/\/doi.org\/10.1007\/978-3-540-68564-7_9","DOI":"10.1007\/978-3-540-68564-7_9"},{"key":"25_CR11","doi-asserted-by":"publisher","unstructured":"Kutzner, C., Apostolov, R., Hess, B., Grubmuller, H.: Scaling of the GROMACS 4.6 molecular dynamics code on superMUC. Adv. Parallel Comput. 25, 722\u2013727 (2014). https:\/\/doi.org\/10.3233\/978-1-61499-381-0-722","DOI":"10.3233\/978-1-61499-381-0-722"},{"issue":"27","key":"25_CR12","doi-asserted-by":"publisher","first-page":"2418","DOI":"10.1002\/jcc.26011","volume":"40","author":"C Kutzner","year":"2019","unstructured":"Kutzner, C., P\u00e1ll, S., Fechner, M., Esztermann, A., de Groot, B.L., Grubmuller, H.: More bang for your buck: Improved use of GPU nodes for GROMACS 2018. J. Comput. Chem. 40(27), 2418\u20132431 (2019). https:\/\/doi.org\/10.1002\/jcc.26011","journal-title":"J. Comput. Chem."},{"key":"25_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-15976-8_1","volume-title":"Solving Software Challenges for Exascale","author":"S P\u00e1ll","year":"2015","unstructured":"P\u00e1ll, S., Abraham, M.J., Kutzner, C., Hess, B., Lindahl, E.: Tackling Exascale software challenges in molecular dynamics simulations with GROMACS. In: Markidis, S., Laure, E. (eds.) EASC 2014. LNCS, vol. 8759, pp. 3\u201327. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-15976-8_1"},{"key":"25_CR14","doi-asserted-by":"publisher","unstructured":"Phillips, J.C., et al.: Scalable molecular dynamics with NAMD. J. Comput. Chem. 26(16), 1781\u20131802 (2005). https:\/\/doi.org\/10.1002\/jcc.20289","DOI":"10.1002\/jcc.20289"},{"key":"25_CR15","unstructured":"Shamshirgar, D.S., Hess, B., Tornberg, A.K.: A comparison of the spectral EWALD and smooth particle mesh EWALD methods in GROMACS. arXiv preprint arXiv:1712.04718 (2017). 10.48550\/arXiv. 1712.04718"},{"key":"25_CR16","doi-asserted-by":"publisher","unstructured":"Smith, S.A., Cromey, C.E., Lowenthal, D.K., Domke, J., Jain, N., Thiagarajan, J.J., Bhatele, A.: Mitigating inter-job interference using adaptive flow-aware routing. In: SC 2018: International Conference for High Performance Computing, Networking, Storage and Analysis (2018). https:\/\/doi.org\/10.1109\/SC.2018.00030","DOI":"10.1109\/SC.2018.00030"},{"key":"25_CR17","doi-asserted-by":"publisher","unstructured":"Swarztrauber, P.N.: Vectorizing the FFTs. In: Rodrigue, G. (ed.) Parallel Computations, pp. 51\u201383. Academic Press (1982). https:\/\/doi.org\/10.1016\/B978-0-12-592101-5.50007-5","DOI":"10.1016\/B978-0-12-592101-5.50007-5"},{"issue":"16","key":"25_CR18","doi-asserted-by":"publisher","first-page":"1701","DOI":"10.1002\/jcc.20291","volume":"26","author":"D Van Der Spoel","year":"2005","unstructured":"Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A.E., Berendsen, H.J.: Gromacs: fast, flexible, and free. J. Comput. Chem. 26(16), 1701\u20131718 (2005). https:\/\/doi.org\/10.1002\/jcc.20291","journal-title":"J. Comput. Chem."},{"issue":"4","key":"25_CR19","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1177\/1094342011429952","volume":"26","author":"R Yokota","year":"2012","unstructured":"Yokota, R., Barba, L.A.: A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems. Int. J. High Perform. Comput. Appl. 26(4), 337\u2013346 (2012). https:\/\/doi.org\/10.1177\/1094342011429952","journal-title":"Int. J. High Perform. Comput. Appl."}],"container-title":["Lecture Notes in Computer Science","Parallel Processing and Applied Mathematics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-30442-2_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T10:04:36Z","timestamp":1682589876000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-30442-2_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031304415","9783031304422"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-30442-2_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"28 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PPAM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Parallel Processing and Applied Mathematics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gdansk","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Poland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ppam2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ppam.edu.pl\/","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":"132","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":"77","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":"58% - 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":"3","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":"2","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}