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Parallélisation hybride d'une application de détection de noyaux cellulaires

Daniel Salas 1
1 CAMUS - Compilation pour les Architectures MUlti-coeurS
Inria Nancy - Grand Est, ICube - Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie
Abstract : The parallelized version of the Marked Point Process algorithm in shared memory is able to speedup cells nuclei detection. However, the limitations imposed by the number of CPU cores or the memory capacity of GPU cards do not allow the analysis of an entire histological image (50,000 × 50,000 pixels). To achieve this, we propose to add a distributed dimension to this parallelization using the hybrid Ordered Read-Write Locks model. In order to guarantee the validity of the original algorithm, we have implemented different strategies to ensure that all nuclei are processed and that local processing is considered on a global scale. The tests carried out first validated the scalability of the application and then showed an acceleration factor of 40 on 64 CPU cores.
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Contributor : Daniel Salas <>
Submitted on : Thursday, November 28, 2019 - 2:54:35 PM
Last modification on : Friday, October 23, 2020 - 4:38:14 PM
Long-term archiving on: : Saturday, February 29, 2020 - 5:08:27 PM


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  • HAL Id : tel-02384725, version 1


Daniel Salas. Parallélisation hybride d'une application de détection de noyaux cellulaires. Calcul parallèle, distribué et partagé [cs.DC]. Université de Strasbourg, 2019. Français. ⟨tel-02384725⟩



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