Containerization on a Self-supervised active foveated approach to Computer Vision

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dc.contributor.authorDematties, Dario
dc.contributor.authorRizzi, Silvio
dc.contributor.authorThiruvathukal, George K.
dc.contributor.orcidDematties, Dario [0000-0002-8726-7837]spa
dc.contributor.orcidRizzi, Silvio [0000-0002-3804-2471]spa
dc.contributor.orcidThiruvathukal, George K. [0000-0002-0452-5571]spa
dc.date.accessioned2024-09-19T20:55:49Z
dc.date.available2024-09-19T20:55:49Z
dc.date.issued2024-06-18
dc.description.abstractenglishScaling complexity and appropriate data sets availability for training current Computer Vision (CV) applications poses major challenges. We tackle these challenges finding inspiration in biology and introducing a Self-supervised (SS) active foveated approach for CV. In this paper we present our solution to achieve portability and reproducibility by means of containerization utilizing Singularity. We also show the parallelization scheme used to run our models on ThetaGPU–an Argonne Leadership Computing Facility (ALCF) machine of 24 NVIDIA DGX A100 nodes. We describe how to use mpi4py to provide DistributedDataParallel (DDP) with all the needed information about world size as well as global and local ranks. We also show our dual pipe implementation of a foveator using NVIDIA Data Loading Library (DALI). Finally we conduct a series of strong scaling tests on up to 16 ThetaGPU nodes (128 GPUs), and show some variability trends in parallel scaling efficiency.eng
dc.format.mimetypeapplication/pdfspa
dc.identifier.doihttps://doi.org/10.29375/25392115.5055
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga UNABspa
dc.identifier.issnISSN: 1657-2831spa
dc.identifier.issne-ISSN: 2539-2115spa
dc.identifier.repourlrepourl:https://repository.unab.edu.cospa
dc.identifier.urihttp://hdl.handle.net/20.500.12749/26652
dc.language.isospaspa
dc.publisherUniversidad Autónoma de Bucaramanga UNABspa
dc.relationhttps://revistas.unab.edu.co/index.php/rcc/article/view/5055/3966spa
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dc.relation.urihttps://revistas.unab.edu.co/index.php/rcc/issue/view/297spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.sourceVol. 25 Núm. 1 (2024): Revista Colombiana de Computación (Enero-Junio); 29-38spa
dc.subject.keywordsSingularity Containerizationeng
dc.subject.keywordsNVIDIA DALIeng
dc.subject.keywordsData Loading and Pre-processing Libraryeng
dc.subject.keywordsHigh Performance Computing, Strong Scalingeng
dc.titleContainerization on a Self-supervised active foveated approach to Computer Visioneng
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.driverinfo:eu-repo/semantics/article
dc.type.hasversioninfo:eu-repo/semantics/publishedVersion
dc.type.localArtículospa
dc.type.redcolhttp://purl.org/redcol/resource_type/ART

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