Project-team TOPAL Tools and Optimization for high Performance Applications and Learning Tools and Optimization for high Performance Applications and Learning
The aim of the Topal team (Inria, Université de Bordeaux, Bordeaux INP, LaBRI) is to propose efficient algorithms and tools for linear and tensor algebra on the one hand (with PaStiX and Chameleon) in particular), and for training on the other (with rockmate). Centre(s) inria Inria Centre at the University of Bordeaux In partnership with Institut Polytechnique de Bordeaux,Université de Bordeaux Publications HALActivity reportsTeam's website Contacts Olivier Beaumont Team leader Catherine Cattaert Megrat Team assistant News Artificial intelligence © sdecoret - stock.adobe.com AI and high-performance computing: two closely linked fields? 06/03/2024 Job opportunities Post-Doctoral Research Visit F/M Efficient Deep Learning (IDP 2024) Deadline to apply 03/05/2024 Job opportunities PhD Position F/M Efficient Deep Learning (IDP 2024) Deadline to apply 03/05/2024 Optimization © Qarnot Computing PULSE: a Challenge to reduce, control and valorize the environmental emissions of intensive computing 24/10/2022 See more news Discover similar project-teams about the same theme
Artificial intelligence © sdecoret - stock.adobe.com AI and high-performance computing: two closely linked fields? 06/03/2024
Job opportunities Post-Doctoral Research Visit F/M Efficient Deep Learning (IDP 2024) Deadline to apply 03/05/2024
Optimization © Qarnot Computing PULSE: a Challenge to reduce, control and valorize the environmental emissions of intensive computing 24/10/2022
