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Communication Dans Un Congrès Année : 2023

Une implémentation GPU de la méthode de recherche approximative FlyHash

Résumé

FlyHash is a locality-sensitive hashing algorithm inspired by the nervous system of the Drosophila fly. It has demonstrated to be particularly effective for similarity search, especially in the federated context where multiple players collaborate to solve a statistical learning task. FlyHash mainly relies on a process called winner-take-all, which is used to binarize information. However, the implementation of this process is a major challenge and limits the algorithm's usage in processing large data streams. In this paper, we propose a simple algorithm to make the winner-take-all operation efficient on GPUs. We create a FlyHash adaptation suitable for the CUDA architecture. We assess the speed of this version experimentally and present a comparison with the CPU version of FlyHash.
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Dates et versions

hal-04328529 , version 1 (07-12-2023)

Identifiants

  • HAL Id : hal-04328529 , version 1

Citer

Arthur da Cunha, Damien Rivet, Emanuele Natale, Aurora Rossi. Une implémentation GPU de la méthode de recherche approximative FlyHash. CAID 2023 - 5e Conference on Artificial Intelligence for Defense, DGA Maîtrise de l'Information, Nov 2023, Rennes, France. ⟨hal-04328529⟩
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