| Article | |
| Report number | CERN-OPEN-2022-014 |
| Title | Acceleration with GPUs and other RooFit news |
| Author(s) | Michalainas, Emmanouil (Aristotle University of Thessaloniki (GR)) ; Rembser, Jonas (CERN) ; Hageboeck, Stephan (CERN) ; Moneta, Lorenzo (CERN) |
| Publication | 2023 |
| Imprint | 01 Feb 2022 |
| Number of pages | 6 |
| Published in: | J.Phys.Conf.Ser. 2438 (2023) 012066 |
| Presented at | 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021), Daejeon, Korea, 29 Nov - 3 Dec 2021, pp.012066 |
| DOI | 10.1088/1742-6596/2438/1/012066 |
| Subject category | Computing and Computers |
| Abstract | RooFit is a toolkit for statistical modeling and fitting, and together with RooStats it is used for measurements and statistical tests by most experiments in particle physics, particularly the LHC experiments. As the LHC program progresses, physics analysis becomes more computationally demanding. Therefore, RooFit development in recent years is focused on modernizing RooFit, improving its ease of use, and on performance optimization. This paper presents the new RooFit vectorized computation mode, which supports calculations on the GPU. Additionally, we discuss new features in the upcoming ROOT 6.26 release, highlighting the new pythonizations in particular. |
| Other source | Inspire |
| Submitted by | [email protected] |
Datensatz erzeugt am 2022-11-09, letzte Änderung am 2023-08-22
