{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T18:12:06Z","timestamp":1783534326600,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":33,"publisher":"ACM","funder":[{"DOI":"10.13039\/100002418","name":"Intel Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002418","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Swedish Foundation for Stragetic Research"},{"DOI":"10.13039\/100017156","name":"Swedish e-Science Research Centre","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100017156","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Academic Infrastructure for Supercomputing in Sweden","award":["2023\/3-27"],"award-info":[{"award-number":["2023\/3-27"]}]},{"name":"HORIZON EUROPE","award":["HORIZON-EUROHPC-JU-2021-COE-01-02"],"award-info":[{"award-number":["HORIZON-EUROHPC-JU-2021-COE-01-02"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,5]]},"DOI":"10.1145\/3725789.3725797","type":"proceedings-article","created":{"date-parts":[[2025,8,16]],"date-time":"2025-08-16T06:24:06Z","timestamp":1755325446000},"page":"71-84","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4906-7241","authenticated-orcid":false,"given":"Andrey","family":"Alekseenko","sequence":"first","affiliation":[{"name":"KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0603-5514","authenticated-orcid":false,"given":"Szil\u00e1rd","family":"P\u00e1ll","sequence":"additional","affiliation":[{"name":"KTH Royal Institute of Technology, PDC Center for High Performance Computing, Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2734-2794","authenticated-orcid":false,"given":"Erik","family":"Lindahl","sequence":"additional","affiliation":[{"name":"KTH Royal Institute of Technology, Stockholm, Sweden and Stockholm University, Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,8,15]]},"reference":[{"key":"e_1_3_3_2_2_2","unstructured":"Mark Abraham Andrey Alekseenko Vladimir Basov Cathrine Bergh Eliane Briand Ania Brown Mahesh Doijade Giacomo Fiorin Stefan Fleischmann Sergey Gorelov Gilles Gouaillardet Alan Gray M.\u00a0Eric Irrgang Farzaneh Jalalypour Joe Jordan Carsten Kutzner Justin\u00a0A. Lemkul Magnus Lundborg Pascal Merz Vedran Miletic Dmitry Morozov Julien Nabet Szil\u00e1rd P\u00e1ll Andrea Pasquadibisceglie Michele Pellegrino Hubert Santuz Roland Schulz Tatiana Shugaeva Alexey Shvetsov Alessandra Villa Sebastian Wingbermuehle Berk Hess and Erik Lindahl. 2024. GROMACS 2024.0 Source code. https:\/\/doi.org\/10.5281\/zenodo.10589643"},{"key":"e_1_3_3_2_3_2","unstructured":"Mark Abraham Andrey Alekseenko Vladimir Basov Cathrine Bergh Eliane Briand Ania Brown Mahesh Doijade Giacomo Fiorin Stefan Fleischmann Sergey Gorelov Gilles Gouaillardet Alan Gray M.\u00a0Eric Irrgang Farzaneh Jalalypour Joe Jordan Carsten Kutzner Justin\u00a0A. Lemkul Magnus Lundborg Pascal Merz Vedran Miletic Dmitry Morozov Julien Nabet Szil\u00e1rd P\u00e1ll Andrea Pasquadibisceglie Michele Pellegrino Hubert Santuz Roland Schulz Tatiana Shugaeva Alexey Shvetsov Alessandra Villa Sebastian Wingbermuehle Berk Hess and Erik Lindahl. 2024. GROMACS 2024.1 Source code. https:\/\/doi.org\/10.5281\/zenodo.10721181"},{"key":"e_1_3_3_2_4_2","doi-asserted-by":"crossref","unstructured":"Mark\u00a0James Abraham Teemu Murtola Roland Schulz Szil\u00e1rd P\u00e1ll Jeremy\u00a0C. Smith Berk Hess and Erik Lindahl. 2015. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1\u20132 (Sept. 2015) 19\u201325. https:\/\/doi.org\/10.1016\/j.softx.2015.06.001","DOI":"10.1016\/j.softx.2015.06.001"},{"key":"e_1_3_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3585341.3585350"},{"key":"e_1_3_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3456669.3456690"},{"key":"e_1_3_3_2_7_2","unstructured":"Andrey Alekseenko and Szil\u00e1rd P\u00e1ll. 2022. Progress towards extending GPU support in GROMACS with SYCL. https:\/\/doi.org\/10.6084\/m9.figshare.20170541.v1 Poster presented at the PASC\u201922 conference."},{"key":"e_1_3_3_2_8_2","unstructured":"Aksel Alpay. 2023. AdaptiveCpp 23.10.0. https:\/\/github.com\/AdaptiveCpp\/AdaptiveCpp\/releases\/tag\/v23.10.0 Accessed 2024-04-07."},{"key":"e_1_3_3_2_9_2","unstructured":"Aksel Alpay. 2023. AdaptiveCpp (hipSYCL) 0.9.4. https:\/\/github.com\/AdaptiveCpp\/AdaptiveCpp\/releases\/tag\/v0.9.4 Accessed 2024-04-07]."},{"key":"e_1_3_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3388333.3388658"},{"key":"e_1_3_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/3585341.3585351"},{"key":"e_1_3_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3529538.3530005"},{"key":"e_1_3_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-50371-0_19"},{"key":"e_1_3_3_2_14_2","unstructured":"Leopold Cambier Doris Pan and \u0141ukasz Ligowski. 2022. Multinode Multi-GPU: Using NVIDIA cuFFTMp FFTs at Scale. https:\/\/developer.nvidia.com\/blog\/multinode-multi-gpu-using-nvidia-cufftmp-ffts-at-scale\/ Accessed: 2024-04-07."},{"key":"e_1_3_3_2_15_2","doi-asserted-by":"crossref","unstructured":"Peter Eastman Raimondas Galvelis Ra\u00fal\u00a0P. Pel\u00e1ez Charlles R.\u00a0A. Abreu Stephen\u00a0E. Farr Emilio Gallicchio Anton Gorenko Michael\u00a0M. Henry Frank Hu Jing Huang Andreas Kr\u00e4mer Julien Michel Joshua\u00a0A. Mitchell Vijay\u00a0S. Pande Jo\u00e3o\u00a0PGLM Rodrigues Jaime Rodriguez-Guerra Andrew\u00a0C. Simmonett Sukrit Singh Jason Swails Philip Turner Yuanqing Wang Ivy Zhang John\u00a0D. Chodera Gianni De\u00a0Fabritiis and Thomas\u00a0E. Markland. 2024. OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The Journal of Physical Chemistry B 128 1 (Jan. 2024) 109\u2013116. https:\/\/doi.org\/10.1021\/acs.jpcb.3c06662 Publisher: American Chemical Society.","DOI":"10.1021\/acs.jpcb.3c06662"},{"key":"e_1_3_3_2_16_2","unstructured":"Alan Gray and Szil\u00e1rd P\u00e1ll. 2023. Cutting-Edge CUDA Technologies for Molecular Dynamics and Beyond. https:\/\/www.nvidia.com\/en-us\/on-demand\/session\/gtcspring23-s51110\/ Accessed: 2024-04-09."},{"key":"e_1_3_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/3624062.3624178"},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"crossref","unstructured":"Berk Hess Carsten Kutzner David Van Der\u00a0Spoel and Erik Lindahl. 2008. GROMACS 4: Algorithms for Highly Efficient Load-Balanced and Scalable Molecular Simulation. Journal of Chemical Theory and Computation 4 3 (2008) 435\u2013447. https:\/\/doi.org\/10.1021\/ct700301q","DOI":"10.1021\/ct700301q"},{"key":"e_1_3_3_2_19_2","unstructured":"Rasmus Kronberg. 2024. Biomolecular Simulations on the LUMI Supercomputer. https:\/\/doi.org\/10.5281\/zenodo.10696768 Poster presented at the CECAM workshop \u201cPerspectives and challenges of future HPC installations for atomistic and molecular simulations\u201d."},{"key":"e_1_3_3_2_20_2","doi-asserted-by":"crossref","unstructured":"Carsten Kutzner Szil\u00e1rd P\u00e1ll Martin Fechner Ansgar Esztermann Bert\u00a0L. de Groot and Helmut Grubm\u00fcller. 2015. Best bang for your buck: GPU nodes for GROMACS biomolecular simulations. Journal of Computational Chemistry 36 26 (2015) 1990\u20132008. https:\/\/doi.org\/10.1002\/jcc.24030","DOI":"10.1002\/jcc.24030"},{"key":"e_1_3_3_2_21_2","doi-asserted-by":"crossref","unstructured":"Carsten Kutzner Szil\u00e1rd P\u00e1ll Martin Fechner Ansgar Esztermann Bert\u00a0L. de Groot and Helmut Grubm\u00fcller. 2019. More bang for your buck: Improved use of GPU nodes for GROMACS 2018. Journal of Computational Chemistry 40 27 (2019) 2418\u20132431. https:\/\/doi.org\/10.1002\/jcc.26011","DOI":"10.1002\/jcc.26011"},{"key":"e_1_3_3_2_22_2","doi-asserted-by":"crossref","unstructured":"Siewert\u00a0J. Marrink Luca Monticelli Manuel\u00a0N. Melo Riccardo Alessandri D.\u00a0Peter Tieleman and Paulo C.\u00a0T. Souza. 2023. Two decades of Martini: Better beads broader scope. WIREs Computational Molecular Science 13 1 (2023) e1620. https:\/\/doi.org\/10.1002\/wcms.1620","DOI":"10.1002\/wcms.1620"},{"key":"e_1_3_3_2_23_2","unstructured":"Naveen Namashivayam Krishna Kandalla Trey White Nick Radcliffe Larry Kaplan and Mark Pagel. 2022. Exploring GPU Stream-Aware Message Passing using Triggered Operations. arxiv:https:\/\/arXiv.org\/abs\/2208.04817\u00a0[cs.DC] https:\/\/arxiv.org\/abs\/2208.04817"},{"key":"e_1_3_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-15976-8_1"},{"key":"e_1_3_3_2_25_2","doi-asserted-by":"crossref","unstructured":"James\u00a0C. Phillips Rosemary Braun Wei Wang James Gumbart Emad Tajkhorshid Elizabeth Villa Christophe Chipot Robert\u00a0D. Skeel Laxmikant Kal\u00e9 and Klaus Schulten. 2005. Scalable molecular dynamics with NAMD. Journal of Computational Chemistry 26 16 (2005) 1781\u20131802. https:\/\/doi.org\/10.1002\/jcc.20289","DOI":"10.1002\/jcc.20289"},{"key":"e_1_3_3_2_26_2","doi-asserted-by":"crossref","unstructured":"James\u00a0C. Phillips David\u00a0J. Hardy Julio D.\u00a0C. Maia John\u00a0E. Stone Jo\u00e3o\u00a0V. Ribeiro Rafael\u00a0C. Bernardi Ronak Buch Giacomo Fiorin J\u00e9r\u00f4me H\u00e9nin Wei Jiang Ryan McGreevy Marcelo C.\u00a0R. Melo Brian\u00a0K. Radak Robert\u00a0D. Skeel Abhishek Singharoy Yi Wang Beno\u00eet Roux Aleksei Aksimentiev Zaida Luthey-Schulten Laxmikant\u00a0V. Kal\u00e9 Klaus Schulten Christophe Chipot and Emad Tajkhorshid. 2020. Scalable molecular dynamics on CPU and GPU architectures with NAMD. The Journal of Chemical Physics 153 4 (July 2020) 044130. https:\/\/doi.org\/10.1063\/5.0014475","DOI":"10.1063\/5.0014475"},{"key":"e_1_3_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3180270.3180271"},{"key":"e_1_3_3_2_28_2","doi-asserted-by":"crossref","unstructured":"Szil\u00e1rd P\u00e1ll Artem Zhmurov Paul Bauer Mark Abraham Magnus Lundborg Alan Gray Berk Hess and Erik Lindahl. 2020. Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS. J. Chem. Phys. 153 13 (Oct. 2020) 134110. https:\/\/doi.org\/10.1063\/5.0018516","DOI":"10.1063\/5.0018516"},{"key":"e_1_3_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4842-9691-2"},{"key":"e_1_3_3_2_30_2","doi-asserted-by":"crossref","unstructured":"Romelia Salomon-Ferrer Andreas\u00a0Walter Goetz Duncan Poole Scott Le\u00a0Grand and Ross\u00a0C Walker. 2013. Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit Solvent Particle Mesh Ewald. Journal of Chemical Theory and Computation 9 9 (Aug. 2013) 130806125930006. https:\/\/doi.org\/10.1021\/ct400314y","DOI":"10.1021\/ct400314y"},{"key":"e_1_3_3_2_31_2","volume-title":"Proceedings of the Cray User Group 2022 Conference","author":"Sedova Ada","year":"2022","unstructured":"Ada Sedova, Russell\u00a0B. Davidson, Mathieu Taillefumier, and Wael Elwasif. 2022. HPC Molecular Simulation Tries Out a New GPU: Experiences on Early AMD Test Systems for the Frontier Supercomputer. In Proceedings of the Cray User Group 2022 Conference. https:\/\/cug.org\/proceedings\/cug2022_proceedings\/includes\/files\/pap113s2-file1.pdf"},{"key":"e_1_3_3_2_32_2","doi-asserted-by":"crossref","unstructured":"Dmitrii Tolmachev. 2023. VkFFT-A Performant Cross-Platform and Open-Source GPU FFT Library. IEEE Access 11 (2023) 12039\u201312058. https:\/\/doi.org\/10.1109\/ACCESS.2023.3242240","DOI":"10.1109\/ACCESS.2023.3242240"},{"key":"e_1_3_3_2_33_2","doi-asserted-by":"crossref","unstructured":"Martin V\u00f6gele J\u00fcrgen K\u00f6finger and Gerhard Hummer. 2018. Hydrodynamics of Diffusion in Lipid Membrane Simulations. Phys. Rev. Lett. 120 (Jun 2018) 268104. Issue 26. https:\/\/doi.org\/10.1103\/PhysRevLett.120.268104","DOI":"10.1103\/PhysRevLett.120.268104"},{"key":"e_1_3_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3555819.3555820"}],"event":{"name":"CUG 2024: Cray User Group","location":"Perth Australia","acronym":"CUG 2024"},"container-title":["Proceedings of the Cray User Group"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3725789.3725797","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,16]],"date-time":"2025-08-16T06:24:27Z","timestamp":1755325467000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3725789.3725797"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,5]]},"references-count":33,"alternative-id":["10.1145\/3725789.3725797","10.1145\/3725789"],"URL":"https:\/\/doi.org\/10.1145\/3725789.3725797","relation":{},"subject":[],"published":{"date-parts":[[2024,5,5]]},"assertion":[{"value":"2025-08-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}