Programming model for the implementation of 2D-3D image processing applications on a hybrid CPU-GPU cluster.
type: Dataset
description: Originally designed to relieve the CPU from graphics rendering tasks, the GPU has becomea massively parallel architecture suitable for processing large amounts of data. While it haswon a significant market share in the High Performance Computing domain, an Algorithm-Architecture Matching approach is still necessary to efficiently implement an algorithm onGPU.The contribution of this thesis is twofold. Firstly, we present the significant gain providedby the implementation of a granulometry optimized algorithm (computation time decreasesfrom several hours to less than minute for a volume of 10243 voxels). An analytical modelestablishing the performance variations of the granulometry application is also presented. Webelieve it can be expanded to other regular algorithms.Secondly, the deployment of Signal and Image processing applications on multi-GPUcluster can be a tedious task for the programmer. In order to help him, we developped alibrary that reduces the scope of the programmer’s contribution in the development. Hisremaining tasks are decomposing the application into a Data Flow Graph and giving mappingannotations in order for the tool to automatically dispatch tasks on the processing elements(GPP or GPU). The throughput of a visual sailency streaming application is then improvedthanks to the efficient implementation brought by our tool on a multi-GPU cluster. In orderto permit dynamic load balancing, a task migration method has also been incorporated into it.
landing page: https://theses.hal.science/tel-00876668
identifier: NNT: 2012GRENT099
keyword: adequation-algorithme-architecture
keyword: algorithm-architecture-matching
keyword: architecture-heterogene
keyword: gpgpu
keyword: heterogeneous-architecture
keyword: infoeu-reposemanticsdoctoralthesis
keyword: modele-de-programmation
keyword: multi-gpu
keyword: programming-model
keyword: spiotherengineering-sciences-physicsother
keyword: theses
issued: 2026-05-09T06:16:45.242136
modified: 2026-05-09T06:16:45.242140
language: fr
contact point: Organization
  fn: CCSD

test_moissonnage_selune
type: Agent

Programming model for the implementation of 2D-3D image processing applications on a hybrid CPU-GPU cluster.
type: Distribution
format: HTML
access URL: https://theses.hal.science/tel-00876668
issued: 2026-05-09T06:16:45.260154
modified: 2026-05-09T06:16:45.224627