معرفی
Samuel Thibault is a Professor at University of Bordeaux, affiliated with Laboratoire Bordelais de Recherche en Informatique (LaBRI) and Inria Bordeaux -- Sud-Ouest. He is a member of the SATANAS team at LaBRI (theme: High Performance Runtime Systems for Parallel Architectures) and the STORM research team at Inria Bordeaux (previously RunTime). His work bridges academic research and practical implementation of high-performance computing systems.
Thibault's research focuses on task-based runtime systems, particularly StarPU, for heterogeneous and parallel computing architectures. His work addresses critical challenges in scheduling algorithms, memory management under constraints, data locality optimization, and performance modeling for complex NUMA architectures. He has made significant contributions to the field of parallel computing through the development and analysis of runtime systems that efficiently manage tasks across diverse hardware resources including CPUs, GPUs, and other accelerators. His research has practical applications in scientific computing, deep learning inference, and large-scale simulations requiring extreme computing power.
His recent publication trends show a strong emphasis on optimizing task-based runtime systems for heterogeneous architectures with particular attention to memory constraints and data locality. There's a clear progression toward applying these techniques to deep learning inference workloads, as evidenced by his StarONNX project. His work consistently addresses the challenge of balancing throughput and latency in complex computing environments, with increasing focus on recursive task graphs and dynamic adaptation strategies.
Thibault is actively involved in European research initiatives including TEXTAROSSA (focusing on exascale technologies) and EXA2PRO (high development productivity on heterogeneous systems). His work has been published consistently in top-tier conferences and journals in parallel and distributed computing.
As part of the STORM team at Inria Bordeaux, Thibault contributes to advancing the state of the art in runtime systems for high-performance computing. His team's work on StarPU has become a reference implementation in the field, enabling researchers and practitioners to develop applications that can efficiently utilize heterogeneous computing resources without needing to manage the complexity of different hardware architectures directly.
