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

Scaling 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 solu...

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Autores:
Dematties, Dario
Rizzi, Silvio
Thiruvathukal, George K.
Tipo de recurso:
Article of investigation
Fecha de publicación:
2024
Institución:
Universidad Autónoma de Bucaramanga - UNAB
Repositorio:
Repositorio UNAB
Idioma:
spa
OAI Identifier:
oai:repository.unab.edu.co:20.500.12749/26652
Acceso en línea:
http://hdl.handle.net/20.500.12749/26652
https://doi.org/10.29375/25392115.5055
Palabra clave:
Singularity Containerization
NVIDIA DALI
Data Loading and Pre-processing Library
High Performance Computing, Strong Scaling
Rights
License
http://purl.org/coar/access_right/c_abf2
id UNAB2_7aae592bc5045beba8f5137d13749a99
oai_identifier_str oai:repository.unab.edu.co:20.500.12749/26652
network_acronym_str UNAB2
network_name_str Repositorio UNAB
repository_id_str
dc.title.eng.fl_str_mv Containerization on a Self-supervised active foveated approach to Computer Vision
title Containerization on a Self-supervised active foveated approach to Computer Vision
spellingShingle Containerization on a Self-supervised active foveated approach to Computer Vision
Singularity Containerization
NVIDIA DALI
Data Loading and Pre-processing Library
High Performance Computing, Strong Scaling
title_short Containerization on a Self-supervised active foveated approach to Computer Vision
title_full Containerization on a Self-supervised active foveated approach to Computer Vision
title_fullStr Containerization on a Self-supervised active foveated approach to Computer Vision
title_full_unstemmed Containerization on a Self-supervised active foveated approach to Computer Vision
title_sort Containerization on a Self-supervised active foveated approach to Computer Vision
dc.creator.fl_str_mv Dematties, Dario
Rizzi, Silvio
Thiruvathukal, George K.
dc.contributor.author.none.fl_str_mv Dematties, Dario
Rizzi, Silvio
Thiruvathukal, George K.
dc.contributor.orcid.spa.fl_str_mv Dematties, Dario [0000-0002-8726-7837]
Rizzi, Silvio [0000-0002-3804-2471]
Thiruvathukal, George K. [0000-0002-0452-5571]
dc.subject.keywords.eng.fl_str_mv Singularity Containerization
NVIDIA DALI
Data Loading and Pre-processing Library
High Performance Computing, Strong Scaling
topic Singularity Containerization
NVIDIA DALI
Data Loading and Pre-processing Library
High Performance Computing, Strong Scaling
description Scaling 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.
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-09-19T20:55:49Z
dc.date.available.none.fl_str_mv 2024-09-19T20:55:49Z
dc.date.issued.none.fl_str_mv 2024-06-18
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https://doi.org/10.29375/25392115.5055
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dc.relation.spa.fl_str_mv https://revistas.unab.edu.co/index.php/rcc/article/view/5055/3966
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dc.relation.references.none.fl_str_mv Alahyane, N., Lemoine- Lardennois, C., Tailhefer, C., Collins, T., Fagard, J., & Doré-Mazars, K. (2016, January). Development and learning of saccadic eye movements in 7- to 42-month-old children. Journal of Vision, 16(1), 6, 1-12. https://doi.org/10.1167/16.1.6
Canfield, R. L., & Haith, M. M. (1991). Young infants' visual expectations for symmetric and asymmetric stimulus sequences. Developmental Psychology, 27(2), 198-208. https://doi.org/10.1037/0012-1649.27.2.198
Canfield, R. L., & Kirkham, N. Z. (2001). Infant Cortical Development and the Prospective Control of Saccadic Eye Movements. Infancy, 2(2), 197-211. https://doi.org/10.1207/S15327078IN0202_5
Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., & Zagoruyko, S. (2020, May 28). arXiv:2005.12872v3 [cs.CV]. End-to-End Object Detection with Transformers. https://doi.org/10.48550/arXiv.2005.12872
Castro, D. C., Walker, I., & Glocker, B. (2020). Causality matters in medical imaging. Nature Communications, 11(3673), 1-10. https://doi.org/10.1038/s41467-020-17478-w
Castro, M., Expósito-Casas, E., López-Martín, E., Lizasoain, L., Navarro-Asencio, E., & Gaviria, J. L. (2015, February). Parental involvement on student academic achievement: A meta-analysis. Educational Research Review, 14, 33-46. https://doi.org/10.1016/j.edurev.2015.01.002
Chen, T., Kornblith, S., Norouzi, M., & Hinton, G. (2020, February 13). A Simple Framework for Contrastive Learning of Visual Representations. In H. Daumé III, & A. Singh (Ed.), Proceedings of the 37 th International Conference on Machine Learning, PMLR 119, 119, pp. 1597-1607. Vienna, Austria. https://doi.org/10.48550/arXiv.2002.05709
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., . . . Houlsby, N. (2021, October 22). An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. International Conference on Learning Representations ICLR 2021 (pp. 1-21). Vienna, Austria: OpenReview. https://doi.org/10.48550/arXiv.2010.11929
Hikosaka, O., Nakamura, K., & Nakahara, H. (2006). Basal Ganglia Orient Eyes to Reward. Journal of Neurophysiology, 95(2), 567-584. https://doi.org/10.1152/jn.00458.2005
Hsiao, J. H.-W., & Cottrell, G. (2008). Two Fixations Suffice in Face Recognition. Psychological Science, 19(10), 998-1006. https://www.jstor.org/stable/40064836
Ikeda, T., & Hikosaka, O. (2003, August 14). Reward-Dependent Gain and Bias of Visual Responses in Primate Superior Colliculus. Neuron, 39(4), 693-700. https://doi.org/10.1016/S0896-6273(03)00464-1
Johnson, M. H. (1995). The inhibition of automatic saccades in early infancy. Developmental Psychobiology, 28(5), 281-291. https://doi.org/10.1002/dev.420280504
Kato, M., Miyashita, N., Hikosaka, O., Matsumura, M., Usui, S., & Kori, A. (1995, January). Eye Movements in Monkeys with Local Dopamine Depletion in the Caudate Nucleus. I. Deficits in Spontaneous Saccades. The Journal of Neuroscience, 15(1), 912-927. https://doi.org/10.1523/JNEUROSCI.15-01-00912.1995
Preuss, M. (2018, December). Updated: 2018-12-27T08:37:12+00:00, Editorial: What is Edge Computing: The Network Edge Explained. (J. Leavitt, Ed.) Cloudswards Web site: https://www.cloudwards.net/what-is-edge-computing/
Provis, J. M., Diaz, C. M., & Dreher, B. (1998, March). Ontogeny of the primate fovea:a central issue in retinal development. Progress in Neurobiology, 54(5), 549-581. https://doi.org/10.1016/S0301-0082(97)00079-8
Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. C., Lamantia, A.-S., McNamara, J. O., & Williams, S. M. (Eds.). (2004). Neuroscience (Third ed.). Sunderland, Massachusetts, USA: Sinauer Associates. https://pages.ucsd.edu/~mboyle/COGS107a/pdf-files/Neuroscience.pdf
Ross-Sheehy, S., Reynolds, E., & Eschman, B. (2020). Evidence for Attentional Phenotypes in Infancy and Their Role in Visual Cognitive Performance. Brain Science, 10(9), 605, 1-24. https://doi.org/10.3390/brainsci10090605
Ross-Sheehy, S., Schneegans, S., & Spencer, J. P. (2015). The Infant Orienting With Attention Task: Assessing the Neural Basis of Spatial Attention in Infancy. Infancy, 20(5), 467-506. https://doi.org/10.1111/infa.12087
Salapatek, P., Aslin, R. N., Simonson, J., & Pulos, E. (1980, December). Infant Saccadic Eye Movements to Visible and Previously Visible Targets. Child Development, 51(4), 1090-1094. https://doi.org/10.2307/1129548
Spotorno, S., Malcolm, G. L., & Tatler, B. W. (2014, February). How context information and target information guide the eyes from the first epoch of search in real-world scenes. Journal of Vision, 14(2), 7, 1-21. https://doi.org/10.1167/14.2.7
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., . . . Polosukhin, I. (2017, June 12). Attention Is All You Need. arXiv(1706.03762 [cs.CL]), 15. https://doi.org/10.48550/arXiv.1706.03762
Weber, R. B., & Daroff, R. B. (1972, March). Corrective movements following refixation saccades: Type and control system analysis. Vision Research, 12(3), 467-475. https://doi.org/10.1016/0042-6989(72)90090-9
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spelling Dematties, Dario0d674028-2916-4cd5-92e2-00a8cf3777b2Rizzi, Silvio1bc59e75-7454-4a7f-b8dc-75280a9b15eaThiruvathukal, George K.ff13bf4f-6254-4721-bc05-b7b64c58047cDematties, Dario [0000-0002-8726-7837]Rizzi, Silvio [0000-0002-3804-2471]Thiruvathukal, George K. [0000-0002-0452-5571]2024-09-19T20:55:49Z2024-09-19T20:55:49Z2024-06-18ISSN: 1657-2831e-ISSN: 2539-2115http://hdl.handle.net/20.500.12749/26652instname:Universidad Autónoma de Bucaramanga UNABrepourl:https://repository.unab.edu.cohttps://doi.org/10.29375/25392115.5055application/pdfspaUniversidad Autónoma de Bucaramanga UNABhttps://revistas.unab.edu.co/index.php/rcc/article/view/5055/3966https://revistas.unab.edu.co/index.php/rcc/issue/view/297Alahyane, N., Lemoine- Lardennois, C., Tailhefer, C., Collins, T., Fagard, J., & Doré-Mazars, K. (2016, January). Development and learning of saccadic eye movements in 7- to 42-month-old children. Journal of Vision, 16(1), 6, 1-12. https://doi.org/10.1167/16.1.6Canfield, R. L., & Haith, M. M. (1991). Young infants' visual expectations for symmetric and asymmetric stimulus sequences. Developmental Psychology, 27(2), 198-208. https://doi.org/10.1037/0012-1649.27.2.198Canfield, R. L., & Kirkham, N. Z. (2001). Infant Cortical Development and the Prospective Control of Saccadic Eye Movements. Infancy, 2(2), 197-211. https://doi.org/10.1207/S15327078IN0202_5Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., & Zagoruyko, S. (2020, May 28). arXiv:2005.12872v3 [cs.CV]. End-to-End Object Detection with Transformers. https://doi.org/10.48550/arXiv.2005.12872Castro, D. C., Walker, I., & Glocker, B. (2020). Causality matters in medical imaging. Nature Communications, 11(3673), 1-10. https://doi.org/10.1038/s41467-020-17478-wCastro, M., Expósito-Casas, E., López-Martín, E., Lizasoain, L., Navarro-Asencio, E., & Gaviria, J. L. (2015, February). Parental involvement on student academic achievement: A meta-analysis. Educational Research Review, 14, 33-46. https://doi.org/10.1016/j.edurev.2015.01.002Chen, T., Kornblith, S., Norouzi, M., & Hinton, G. (2020, February 13). A Simple Framework for Contrastive Learning of Visual Representations. In H. Daumé III, & A. Singh (Ed.), Proceedings of the 37 th International Conference on Machine Learning, PMLR 119, 119, pp. 1597-1607. Vienna, Austria. https://doi.org/10.48550/arXiv.2002.05709Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., . . . Houlsby, N. (2021, October 22). An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. International Conference on Learning Representations ICLR 2021 (pp. 1-21). Vienna, Austria: OpenReview. https://doi.org/10.48550/arXiv.2010.11929Hikosaka, O., Nakamura, K., & Nakahara, H. (2006). Basal Ganglia Orient Eyes to Reward. Journal of Neurophysiology, 95(2), 567-584. https://doi.org/10.1152/jn.00458.2005Hsiao, J. H.-W., & Cottrell, G. (2008). Two Fixations Suffice in Face Recognition. Psychological Science, 19(10), 998-1006. https://www.jstor.org/stable/40064836Ikeda, T., & Hikosaka, O. (2003, August 14). Reward-Dependent Gain and Bias of Visual Responses in Primate Superior Colliculus. Neuron, 39(4), 693-700. https://doi.org/10.1016/S0896-6273(03)00464-1Johnson, M. H. (1995). The inhibition of automatic saccades in early infancy. Developmental Psychobiology, 28(5), 281-291. https://doi.org/10.1002/dev.420280504Kato, M., Miyashita, N., Hikosaka, O., Matsumura, M., Usui, S., & Kori, A. (1995, January). Eye Movements in Monkeys with Local Dopamine Depletion in the Caudate Nucleus. I. Deficits in Spontaneous Saccades. The Journal of Neuroscience, 15(1), 912-927. https://doi.org/10.1523/JNEUROSCI.15-01-00912.1995Preuss, M. (2018, December). Updated: 2018-12-27T08:37:12+00:00, Editorial: What is Edge Computing: The Network Edge Explained. (J. Leavitt, Ed.) Cloudswards Web site: https://www.cloudwards.net/what-is-edge-computing/Provis, J. M., Diaz, C. M., & Dreher, B. (1998, March). Ontogeny of the primate fovea:a central issue in retinal development. Progress in Neurobiology, 54(5), 549-581. https://doi.org/10.1016/S0301-0082(97)00079-8Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. C., Lamantia, A.-S., McNamara, J. O., & Williams, S. M. (Eds.). (2004). Neuroscience (Third ed.). Sunderland, Massachusetts, USA: Sinauer Associates. https://pages.ucsd.edu/~mboyle/COGS107a/pdf-files/Neuroscience.pdfRoss-Sheehy, S., Reynolds, E., & Eschman, B. (2020). Evidence for Attentional Phenotypes in Infancy and Their Role in Visual Cognitive Performance. Brain Science, 10(9), 605, 1-24. https://doi.org/10.3390/brainsci10090605Ross-Sheehy, S., Schneegans, S., & Spencer, J. P. (2015). The Infant Orienting With Attention Task: Assessing the Neural Basis of Spatial Attention in Infancy. Infancy, 20(5), 467-506. https://doi.org/10.1111/infa.12087Salapatek, P., Aslin, R. N., Simonson, J., & Pulos, E. (1980, December). Infant Saccadic Eye Movements to Visible and Previously Visible Targets. Child Development, 51(4), 1090-1094. https://doi.org/10.2307/1129548Spotorno, S., Malcolm, G. L., & Tatler, B. W. (2014, February). How context information and target information guide the eyes from the first epoch of search in real-world scenes. Journal of Vision, 14(2), 7, 1-21. https://doi.org/10.1167/14.2.7Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., . . . Polosukhin, I. (2017, June 12). Attention Is All You Need. arXiv(1706.03762 [cs.CL]), 15. https://doi.org/10.48550/arXiv.1706.03762Weber, R. B., & Daroff, R. B. (1972, March). Corrective movements following refixation saccades: Type and control system analysis. Vision Research, 12(3), 467-475. https://doi.org/10.1016/0042-6989(72)90090-9Vol. 25 Núm. 1 (2024): Revista Colombiana de Computación (Enero-Junio); 29-38Containerization on a Self-supervised active foveated approach to Computer Visioninfo:eu-repo/semantics/articleArtículohttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85Singularity ContainerizationNVIDIA DALIData Loading and Pre-processing LibraryHigh Performance Computing, Strong ScalingScaling 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.http://purl.org/coar/access_right/c_abf2ORIGINALArtículo.pdfArtículo.pdfArtículoapplication/pdf889991https://repository.unab.edu.co/bitstream/20.500.12749/26652/1/Art%c3%adculo.pdf367de7545c5650594eee0187193da7d9MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-8347https://repository.unab.edu.co/bitstream/20.500.12749/26652/2/license.txt855f7d18ea80f5df821f7004dff2f316MD52open accessTHUMBNAILArtículo.pdf.jpgArtículo.pdf.jpgIM Thumbnailimage/jpeg10084https://repository.unab.edu.co/bitstream/20.500.12749/26652/3/Art%c3%adculo.pdf.jpgd6029b3c32104d81d42e932478f8e454MD53open access20.500.12749/26652oai:repository.unab.edu.co:20.500.12749/266522024-09-19 22:03:03.823open accessRepositorio Institucional | Universidad Autónoma de Bucaramanga - UNABrepositorio@unab.edu.coTGEgUmV2aXN0YSBDb2xvbWJpYW5hIGRlIENvbXB1dGFjacOzbiBlcyBmaW5hbmNpYWRhIHBvciBsYSBVbml2ZXJzaWRhZCBBdXTDs25vbWEgZGUgQnVjYXJhbWFuZ2EuIEVzdGEgUmV2aXN0YSBubyBjb2JyYSB0YXNhIGRlIHN1bWlzacOzbiB5IHB1YmxpY2FjacOzbiBkZSBhcnTDrWN1bG9zLiBQcm92ZWUgYWNjZXNvIGxpYnJlIGlubWVkaWF0byBhIHN1IGNvbnRlbmlkbyBiYWpvIGVsIHByaW5jaXBpbyBkZSBxdWUgaGFjZXIgZGlzcG9uaWJsZSBncmF0dWl0YW1lbnRlIGludmVzdGlnYWNpw7NuIGFsIHDDumJsaWNvIGFwb3lhIGEgdW4gbWF5b3IgaW50ZXJjYW1iaW8gZGUgY29ub2NpbWllbnRvIGdsb2JhbC4=

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