Thomas Bouvier
Présentation
My main current research interests are related to deployment and scheduling strategies for AI workloads on heterogeneous resources (HPC, cloud, fog, edge). Relevant topics:
Publications
Publications
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Efficient Distributed Continual Learning for Steering Experiments in Real-TimeFuture Generation Computer Systems, 2024, pp.1-19. ⟨10.1016/j.future.2024.07.016⟩ |
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Efficient Data-Parallel Continual Learning with Asynchronous Distributed Rehearsal BuffersCCGrid 2024 - IEEE 24th International Symposium on Cluster, Cloud and Internet Computing, May 2024, Philadelphia (PA), United States. pp.1-10, ⟨10.1109/CCGrid59990.2024.00036⟩ |
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Deploying Heterogeneity-aware Deep Learning Workloads on the Computing ContinuumBDA 2021 - 37e Conférence sur la Gestion de Données - Principes, Technologies et Applications, Oct 2021, Paris, France |
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Heterogeneity-aware Deep Learning Workload Deployments on the Computing ContinuumIPDPS 2021 - 35th IEEE International Parallel and Distributed Processing Symposium, May 2021, Virtual / Portland, United States |