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:

Cloud data services and big data analytics

Stream processing

Parallel and distributed deep learning

Online learning

Workflow management and placement strategies

Publications

Article dans une revue (1)

Efficient Distributed Continual Learning for Steering Experiments in Real-Time Thomas Bouvier,Bogdan Nicolae,Alexandru Costan,Tekin Bicer,Ian Fosteret al. Future Generation Computer Systems, 2024, pp.1-19. ⟨10.1016/j.future.2024.07.016⟩ Article dans une revue hal-04664176v2

Communication dans un congrès (2)

Efficient Data-Parallel Continual Learning with Asynchronous Distributed Rehearsal Buffers Thomas Bouvier,Bogdan Nicolae,Hugo Chaugier,Alexandru Costan,Ian Fosteret al. CCGrid 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⟩ Communication dans un congrès hal-04600107v1
Deploying Heterogeneity-aware Deep Learning Workloads on the Computing Continuum Thomas Bouvier,Alexandru Costan,Gabriel Antoniu BDA 2021 - 37e Conférence sur la Gestion de Données - Principes, Technologies et Applications, Oct 2021, Paris, France Communication dans un congrès hal-03338520v2

Poster de conférence (1)

Heterogeneity-aware Deep Learning Workload Deployments on the Computing Continuum Thomas Bouvier,Alexandru Costan,Gabriel Antoniu IPDPS 2021 - 35th IEEE International Parallel and Distributed Processing Symposium, May 2021, Virtual / Portland, United States Poster de conférence hal-03270129v1