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My research focuses on exploring clustering techniques based on Synchronous Dataflow (SDF), which aims to provide a universal description of an application that is portable across various architecture types. These clustering techniques enable the resulting granularity description to seamlessly align with the target architecture.
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Automated level-based clustering of dataflow actors for controlled scheduling complexityJournal of Systems Architecture, 2024, pp.103217. ⟨10.1016/j.sysarc.2024.103217⟩
Article dans une revue
hal-04629332
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Automated Deployment of Radio Astronomy Pipeline on CPU-GPU Processing Systems: DiFX as a Case StudyAstronomical Data Analysis Software & Systems (ADASS) XXXIV, Nov 2024, La Valetta, Malta
Communication dans un congrès
hal-04744986
v1
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SCAPE: HW-Aware Clustering of Dataflow Actors for Tunable Scheduling ComplexityDASIP 2023 - Workshop on Design and Architectures for Signal and Image Processing, HiPEAC, Jan 2023, Toulouse, France. pp.3-14, ⟨10.1007/978-3-031-29970-4_1⟩
Communication dans un congrès
hal-04089941
v1
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Automated Clustering and Pipelining of Dataflow Actors for Controlled Scheduling ComplexityEUSIPCO, EURASIP, Sep 2023, Helsiinki, Finland
Communication dans un congrès
hal-04253298
v1
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