| Capturing phase behavior of ternary lipid mixtures with a refined martini coarse-grained force field TS Carpenter, CA López, C Neale, C Montour, HI Ingólfsson, F Di Natale, ... Journal of chemical theory and computation 14 (11), 6050-6062, 2018 | 77 | 2018 |
| A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer F Di Natale, H Bhatia, TS Carpenter, C Neale, S Kokkila Schumacher, ... Supercomputing: The International Conference for High Performance Computing …, 2019 | 69 | 2019 |
| Machine learning–driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins HI Ingólfsson, C Neale, TS Carpenter, R Shrestha, CA López, TH Tran, ... Proceedings of the National Academy of Sciences 119 (1), e2113297119, 2022 | 66 | 2022 |
| A community roadmap for scientific workflows research and development RF Da Silva, H Casanova, K Chard, I Altintas, RM Badia, B Balis, ... 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 81-90, 2021 | 43 | 2021 |
| Enabling machine learning-ready HPC ensembles with Merlin JL Peterson, B Bay, J Koning, P Robinson, J Semler, J White, R Anirudh, ... Future Generation Computer Systems 131, 255-268, 2022 | 29 | 2022 |
| Generalizable coordination of large multiscale workflows: challenges and learnings at scale H Bhatia, F Di Natale, JY Moon, X Zhang, JR Chavez, F Aydin, C Stanley, ... Proceedings of the International Conference for High Performance Computing …, 2021 | 27 | 2021 |
| Merlin: enabling machine learning-ready HPC ensembles JL Peterson, K Athey, PT Bremer, V Castillo, F Di Natale, JE Field, D Fox, ... Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2019 | 25 | 2019 |
| Workflows community summit: Bringing the scientific workflows community together RF da Silva, H Casanova, K Chard, D Laney, D Ahn, S Jha, C Goble, ... arXiv preprint arXiv:2103.09181, 2021 | 24 | 2021 |
| Comparing gpu power and frequency capping: A case study with the mummi workflow T Patki, Z Frye, H Bhatia, F Di Natale, J Glosli, H Ingolfsson, B Rountree 2019 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS), 31-39, 2019 | 23 | 2019 |
| Machine learning-driven multiscale modeling: bridging the scales with a next-generation simulation infrastructure HI Ingólfsson, H Bhatia, F Aydin, T Oppelstrup, CA López, LG Stanton, ... Journal of Chemical Theory and Computation 19 (9), 2658-2675, 2023 | 19 | 2023 |
| Workflows community summit: Advancing the state-of-the-art of scientific workflows management systems research and development RF da Silva, H Casanova, K Chard, T Coleman, D Laney, D Ahn, S Jha, ... arXiv preprint arXiv:2106.05177, 2021 | 18 | 2021 |
| Maestro workflow conductor F Di Natale Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States), 2017 | 18* | 2017 |
| Exploring CRD mobility during RAS/RAF engagement at the membrane K Nguyen, CA López, C Neale, QN Van, TS Carpenter, F Di Natale, ... Biophysical Journal 121 (19), 3630-3650, 2022 | 12 | 2022 |
| Asynchronous reciprocal coupling of Martini 2.2 coarse-grained and CHARMM36 all-atom simulations in an automated multiscale framework CA López, X Zhang, F Aydin, R Shrestha, QN Van, CB Stanley, ... Journal of Chemical Theory and Computation 18 (8), 5025-5045, 2022 | 8 | 2022 |
| DFMan: A graph-based optimization of dataflow scheduling on high-performance computing systems F Chowdhury, F Di Natale, A Moody, K Mohror, W Yu 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2022 | 8 | 2022 |
| Emulating I/O behavior in scientific workflows on high performance computing systems F Chowdhury, Y Zhu, F Di Natale, A Moody, E Gonsiorowski, K Mohror, ... 2020 IEEE/ACM Fifth International Parallel Data Systems Workshop (PDSW), 34-39, 2020 | 7 | 2020 |
| Scalable composition and analysis techniques for massive scientific workflows DH Ahn, X Zhang, J Mast, S Herbein, F Di Natale, D Kirshner, SA Jacobs, ... 2022 IEEE 18th International Conference on e-Science (e-Science), 32-43, 2022 | 4 | 2022 |
| Understanding I/O Behavior in Scientific Workflows on High Performance Computing Systems F Chowdhury, F Di Natale, A Moody, E Gonsiorowski, K Mohror, W Yu Proceedings of the International Conference on High Performance Computing …, 2019 | 2 | 2019 |
| Multiscale Machine-Learned Modeling Infrastructure RAS JY Moon, F Di Natale, HI Ingolfsson, H Bhatia, JR Chavez Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States), 2021 | 1 | 2021 |
| Adaptable coordination of large multiscale ensembles: challenges and learnings at scale H Bhatia, F Di Natale, JY Moon, X Zhang, JR Chavez, F Aydin, C Stanley, ... Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2021 | 1 | 2021 |
Helgi I. IngólfssonLawrence Livermore National Laboratory在 llnl.gov 的电子邮件经过验证
