Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks
- Autores
- Petrocelli, David; De Giusti, Armando Eduardo; Naiouf, Marcelo
- Año de publicación
- 2020
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Compute-heavy workloads are traditionally run on x86-based HPC platforms and Intel, AMD or Nvidia GPUs; these require a high initial capital expense and ongoing maintenance costs. ARM-based mobile devicesoffer a rad-ically different paradigm with substantially lower capital and maintenance costs and higher gains in performance and efficiency in recent years. When compared to their x-86 brethren, they have become ubiquitous in consumer markets and are making steady gains in the server market. Given this shifting computer paradigm, it is conceivable that a cost- and power-efficient solution for our world’s data processing would include those very same ARM-based mobile devices while they are idling. Given that context, we developed and deployed an auto-scalable, distributed and redundant platform on the basis of a cloud-based service managed via container orchestration and microservices that are in charge of recycling and optimizing these idle resources. We tested the platform performing distributed video compression. We concluded the system allows for improvements in terms of scalability, flexibility, stability, efficiency, and cost for compute-heavy work-loads.
Instituto de Investigación en Informática
Instituto de Investigación en Informática - Materia
-
Ciencias Informáticas
Kubernetes & Containers
Pipelines
Microservices
Cloud Computing & Storage
Mobile Computing
Distributed & Collaborative Computing - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/104766
Ver los metadatos del registro completo
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Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasksPetrocelli, DavidDe Giusti, Armando EduardoNaiouf, MarceloCiencias InformáticasKubernetes & ContainersPipelinesMicroservicesCloud Computing & StorageMobile ComputingDistributed & Collaborative ComputingCompute-heavy workloads are traditionally run on x86-based HPC platforms and Intel, AMD or Nvidia GPUs; these require a high initial capital expense and ongoing maintenance costs. ARM-based mobile devicesoffer a rad-ically different paradigm with substantially lower capital and maintenance costs and higher gains in performance and efficiency in recent years. When compared to their x-86 brethren, they have become ubiquitous in consumer markets and are making steady gains in the server market. Given this shifting computer paradigm, it is conceivable that a cost- and power-efficient solution for our world’s data processing would include those very same ARM-based mobile devices while they are idling. Given that context, we developed and deployed an auto-scalable, distributed and redundant platform on the basis of a cloud-based service managed via container orchestration and microservices that are in charge of recycling and optimizing these idle resources. We tested the platform performing distributed video compression. We concluded the system allows for improvements in terms of scalability, flexibility, stability, efficiency, and cost for compute-heavy work-loads.Instituto de Investigación en InformáticaInstituto de Investigación en Informática2020-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf10-13http://sedici.unlp.edu.ar/handle/10915/104766enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-1927-4info:eu-repo/semantics/reference/hdl/10915/103585info:eu-repo/semantics/reference/hdl/10915/103585info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:55:06Zoai:sedici.unlp.edu.ar:10915/104766Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:55:07.218SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks |
title |
Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks |
spellingShingle |
Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks Petrocelli, David Ciencias Informáticas Kubernetes & Containers Pipelines Microservices Cloud Computing & Storage Mobile Computing Distributed & Collaborative Computing |
title_short |
Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks |
title_full |
Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks |
title_fullStr |
Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks |
title_full_unstemmed |
Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks |
title_sort |
Collaborative, distributed and scalable platform based on mobile, cloud, micro services and containers for intensive computing tasks |
dc.creator.none.fl_str_mv |
Petrocelli, David De Giusti, Armando Eduardo Naiouf, Marcelo |
author |
Petrocelli, David |
author_facet |
Petrocelli, David De Giusti, Armando Eduardo Naiouf, Marcelo |
author_role |
author |
author2 |
De Giusti, Armando Eduardo Naiouf, Marcelo |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Kubernetes & Containers Pipelines Microservices Cloud Computing & Storage Mobile Computing Distributed & Collaborative Computing |
topic |
Ciencias Informáticas Kubernetes & Containers Pipelines Microservices Cloud Computing & Storage Mobile Computing Distributed & Collaborative Computing |
dc.description.none.fl_txt_mv |
Compute-heavy workloads are traditionally run on x86-based HPC platforms and Intel, AMD or Nvidia GPUs; these require a high initial capital expense and ongoing maintenance costs. ARM-based mobile devicesoffer a rad-ically different paradigm with substantially lower capital and maintenance costs and higher gains in performance and efficiency in recent years. When compared to their x-86 brethren, they have become ubiquitous in consumer markets and are making steady gains in the server market. Given this shifting computer paradigm, it is conceivable that a cost- and power-efficient solution for our world’s data processing would include those very same ARM-based mobile devices while they are idling. Given that context, we developed and deployed an auto-scalable, distributed and redundant platform on the basis of a cloud-based service managed via container orchestration and microservices that are in charge of recycling and optimizing these idle resources. We tested the platform performing distributed video compression. We concluded the system allows for improvements in terms of scalability, flexibility, stability, efficiency, and cost for compute-heavy work-loads. Instituto de Investigación en Informática Instituto de Investigación en Informática |
description |
Compute-heavy workloads are traditionally run on x86-based HPC platforms and Intel, AMD or Nvidia GPUs; these require a high initial capital expense and ongoing maintenance costs. ARM-based mobile devicesoffer a rad-ically different paradigm with substantially lower capital and maintenance costs and higher gains in performance and efficiency in recent years. When compared to their x-86 brethren, they have become ubiquitous in consumer markets and are making steady gains in the server market. Given this shifting computer paradigm, it is conceivable that a cost- and power-efficient solution for our world’s data processing would include those very same ARM-based mobile devices while they are idling. Given that context, we developed and deployed an auto-scalable, distributed and redundant platform on the basis of a cloud-based service managed via container orchestration and microservices that are in charge of recycling and optimizing these idle resources. We tested the platform performing distributed video compression. We concluded the system allows for improvements in terms of scalability, flexibility, stability, efficiency, and cost for compute-heavy work-loads. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-09 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/104766 |
url |
http://sedici.unlp.edu.ar/handle/10915/104766 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/isbn/978-950-34-1927-4 info:eu-repo/semantics/reference/hdl/10915/103585 info:eu-repo/semantics/reference/hdl/10915/103585 |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 10-13 |
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