{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:22:29Z","timestamp":1774120949368,"version":"3.50.1"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031408427","type":"print"},{"value":"9783031408434","type":"electronic"}],"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\/978-3-031-40843-4_4","type":"book-chapter","created":{"date-parts":[[2023,8,24]],"date-time":"2023-08-24T12:02:32Z","timestamp":1692878552000},"page":"42-55","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Case Study on\u00a0PMIx-Usage for\u00a0Dynamic Resource Management"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9696-9382","authenticated-orcid":false,"given":"Dominik","family":"Huber","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2390-6716","authenticated-orcid":false,"given":"Martin","family":"Schreiber","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9013-435X","authenticated-orcid":false,"given":"Martin","family":"Schulz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,25]]},"reference":[{"key":"4_CR1","unstructured":"asyncio - asynchronous i\/o. https:\/\/docs.python.org\/3\/library\/asyncio.html"},{"key":"4_CR2","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.parco.2018.08.002","volume":"79","author":"RH Castain","year":"2018","unstructured":"Castain, R.H., Solt, D., Hursey, J., Bouteiller, A.: PMIx: process management for exascale environments. Parallel Comput. 79, 9\u201329 (2018). https:\/\/doi.org\/10.1016\/j.parco.2018.08.002","journal-title":"Parallel Comput."},{"key":"4_CR3","doi-asserted-by":"publisher","unstructured":"Ahn, D.H., Garlick, J., Grondona, M., Lipari, D., Springmeyer, B., Schulz, M.: Flux: a next-generation resource management framework for large HPC centers. In: 2014 43rd International Conference on Parallel Processing Workshops, pp. 9\u201317 (2014). https:\/\/doi.org\/10.1109\/ICPPW.2014.15","DOI":"10.1109\/ICPPW.2014.15"},{"key":"4_CR4","doi-asserted-by":"publisher","first-page":"5231","DOI":"10.3390\/app12105231","volume":"12","author":"J Aliaga","year":"2022","unstructured":"Aliaga, J., Castillo, M., Iserte, S., Martin-Alvarez, I., Mayo, R.: A survey on malleability solutions for high-performance distributed computing. Appl. Sci. 12, 5231 (2022). https:\/\/doi.org\/10.3390\/app12105231","journal-title":"Appl. Sci."},{"key":"4_CR5","doi-asserted-by":"publisher","unstructured":"Bampis, E., Dogeas, K., Kononov, A., Lucarelli, G., Pascual, F.: Scheduling malleable jobs under topological constraints. In: 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), Los Alamitos, CA, USA, pp. 316\u2013325. IEEE Computer Society (2020). https:\/\/doi.org\/10.1109\/IPDPS47924.2020.00041","DOI":"10.1109\/IPDPS47924.2020.00041"},{"key":"4_CR6","unstructured":"PMIx Administrative Steering Committee: PMIx-based reference runtime environment (PRRTE) (2023). https:\/\/github.com\/pmix\/prrte. Accessed 21 Apr 2023"},{"key":"4_CR7","unstructured":"Dai, Y., et al.: Towards scalable resource management for supercomputers. In: SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, Los Alamitos, CA, USA, pp. 324\u2013338. IEEE Computer Society (2022). https:\/\/www.google.com\/url?sa=t &source=web &rct=j &opi=89978449 &url=https:\/\/ieeexplore.ieee.org\/document\/10046103\/ &ved=2ahUKEwjb7PnelsGAAxXEOewKHfDhBpkQFnoECA4QAQ &usg=AOvVaw2gVV4Lq8_DZ9_6NCvwbPNC"},{"key":"4_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.suscom.2020.100447","volume":"28","author":"B Dupont","year":"2020","unstructured":"Dupont, B., Mejri, N., Da Costa, G.: Energy-aware scheduling of malleable HPC applications using a Particle Swarm optimised greedy algorithm. Sustain. Comput. Inform. Syst. 28, 100447 (2020). https:\/\/doi.org\/10.1016\/j.suscom.2020.100447","journal-title":"Sustain. Comput. Inform. Syst."},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Fan, Y., Rich, P., Allcock, W.E., Papka, M.E., Lan, Z.: Hybrid workload scheduling on HPC systems. CoRR abs\/2109.05412 (2021)","DOI":"10.1109\/IPDPS53621.2022.00052"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Fecht, J., Schreiber, M., Schulz, M., Pritchard, H., Holmes, D.J.: An emulation layer for dynamic resources with MPI sessions. In: HPCMALL 2022 - Malleability Techniques Applications in High-Performance Computing, Hambourg, Germany (2022). https:\/\/hal.science\/hal-03856702","DOI":"10.1007\/978-3-031-23220-6_10"},{"key":"4_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1007\/11752578_29","volume-title":"Parallel Processing and Applied Mathematics","author":"RL Graham","year":"2006","unstructured":"Graham, R.L., Woodall, T.S., Squyres, J.M.: Open MPI: a flexible high performance MPI. In: Wyrzykowski, R., Dongarra, J., Meyer, N., Wa\u015bniewski, J. (eds.) PPAM 2005. LNCS, vol. 3911, pp. 228\u2013239. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11752578_29"},{"key":"4_CR12","unstructured":"Huber, D.: Dynamic processes development repository. https:\/\/gitlab.inria.fr\/dynres\/dyn-procs"},{"key":"4_CR13","doi-asserted-by":"publisher","unstructured":"Huber, D., Streubel, M., Compr\u00e9s, I., Schulz, M., Schreiber, M., Pritchard, H.: Towards dynamic resource management with MPI sessions and PMIx. In: Proceedings of the 29th European MPI Users\u2019 Group Meeting, EuroMPI\/USA 2022, pp. 57\u201367. Association for Computing Machinery, New York (2022). https:\/\/doi.org\/10.1145\/3555819.3555856","DOI":"10.1145\/3555819.3555856"},{"key":"4_CR14","unstructured":"Hursey, J.: PMIx docker swarm toy box (2021). https:\/\/github.com\/jjhursey\/pmix-swarm-toy-box"},{"key":"4_CR15","doi-asserted-by":"publisher","unstructured":"Hursey, J.: A separated model for running rootless, unprivileged PMIx-enabled HPC applications in Kubernetes. In: 2022 IEEE\/ACM 4th International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC (CANOPIE-HPC), pp. 36\u201344 (2022). https:\/\/doi.org\/10.1109\/CANOPIE-HPC56864.2022.00009","DOI":"10.1109\/CANOPIE-HPC56864.2022.00009"},{"key":"4_CR16","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.parco.2018.07.006","volume":"78","author":"S Iserte","year":"2018","unstructured":"Iserte, S., Mayo, R., Quintana-Ort\u00ed, E.S., Beltran, V., Pe\u00f1a, A.J.: DMR API: improving cluster productivity by turning applications into malleable. Parallel Comput. 78, 54\u201366 (2018). https:\/\/doi.org\/10.1016\/j.parco.2018.07.006","journal-title":"Parallel Comput."},{"key":"4_CR17","doi-asserted-by":"publisher","unstructured":"Lucas, R., et al.: DOE advanced scientific computing advisory subcommittee (ASCAC) report: top ten exascale research challenges (2014). https:\/\/doi.org\/10.2172\/1222713","DOI":"10.2172\/1222713"},{"issue":"6","key":"4_CR18","doi-asserted-by":"publisher","first-page":"1357","DOI":"10.1109\/TPDS.2018.2793886","volume":"29","author":"L Marchal","year":"2018","unstructured":"Marchal, L., Simon, B., Sinnen, O., Vivien, F.: Malleable task-graph scheduling with a practical speed-up model. IEEE Trans. Parallel Distrib. Syst. 29(6), 1357\u20131370 (2018). https:\/\/doi.org\/10.1109\/TPDS.2018.2793886","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"issue":"4","key":"4_CR19","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1007\/s10951-018-0576-y","volume":"22","author":"V Nagarajan","year":"2018","unstructured":"Nagarajan, V., Wolf, J., Balmin, A., Hildrum, K.: Malleable scheduling for flows of jobs and applications to MapReduce. J. Sched. 22(4), 393\u2013411 (2018). https:\/\/doi.org\/10.1007\/s10951-018-0576-y","journal-title":"J. Sched."},{"key":"4_CR20","doi-asserted-by":"publisher","unstructured":"\u00d6zden, T., Beringer, T., Mazaheri, A., Fard, H.M., Wolf, F.: ElastiSim: a batch-system simulator for malleable workloads. In: Proceedings of the 51st International Conference on Parallel Processing, ICPP 2022. Association for Computing Machinery, New York (2023). https:\/\/doi.org\/10.1145\/3545008.3545046","DOI":"10.1145\/3545008.3545046"},{"key":"4_CR21","unstructured":"PMIx Administrative Steering Committee (ASC): Process management interface for exascale (PMIx) standard version 4.1 (2021). https:\/\/pmix.github.io\/uploads\/2021\/10\/pmix-standard-v4.1.pdf"},{"key":"4_CR22","unstructured":"Prabhakaran, S.: Dynamic resource management and job scheduling for high performance computing. Ph.D. thesis, Technische Universit\u00e4t Darmstadt, Darmstadt (2016). http:\/\/tuprints.ulb.tu-darmstadt.de\/5720\/"},{"issue":"6","key":"4_CR23","doi-asserted-by":"publisher","first-page":"1004","DOI":"10.1007\/s10766-014-0336-3","volume":"43","author":"M Schreiber","year":"2014","unstructured":"Schreiber, M., Riesinger, C., Neckel, T., Bungartz, H.-J., Breuer, A.: Invasive compute balancing for applications with shared and hybrid parallelization. Int. J. Parallel Prog. 43(6), 1004\u20131027 (2014). https:\/\/doi.org\/10.1007\/s10766-014-0336-3","journal-title":"Int. J. Parallel Prog."},{"key":"4_CR24","doi-asserted-by":"publisher","unstructured":"Vallee, G., Gutierrez, C.E.A., Clerget, C.: On-node resource manager for containerized HPC workloads. In: 2019 IEEE\/ACM International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC (CANOPIE-HPC), pp. 43\u201348 (2019). https:\/\/doi.org\/10.1109\/CANOPIE-HPC49598.2019.00011","DOI":"10.1109\/CANOPIE-HPC49598.2019.00011"}],"container-title":["Lecture Notes in Computer Science","High Performance Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-40843-4_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,24]],"date-time":"2023-08-24T12:02:57Z","timestamp":1692878577000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-40843-4_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031408427","9783031408434"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-40843-4_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"25 August 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISC High Performance","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on High Performance Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hamburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 May 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 May 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"38","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"supercomputing2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.isc-hpc.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Linklings","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"70","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":"49","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":"70% - 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)"}}]}}