Using HPC as a Competitive Advantage in an International Robotics Challenge
| Autor: | Jonatan Ginés, Francisco Javier Rodríguez Lera, Miguel Ángel González Santamarta, Vicente Matellán Olivera, Francisco Martín Rico, Ángel Manuel Guerrero Higueras, Claudia Álvarez Aparicio |
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| Rok vydání: | 2021 |
| Předmět: |
Artificial neural network
Computer science business.industry Robotics 02 engineering and technology 010501 environmental sciences Supercomputer 01 natural sciences Competitive advantage Competition (economics) Service-level agreement Knowledge Field Smart city 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Software engineering business 0105 earth and related environmental sciences |
| Zdroj: | Communications in Computer and Information Science ISBN: 9783030680343 |
| DOI: | 10.1007/978-3-030-68035-0_8 |
| Popis: | Researchers in every knowledge field are moving towards the use of supercomputing facilities because the computing power they can provide is not achievable by individual research groups. The use of supercomputing centers would allow them to reduce costs and time. Additionally, there is a growing trend towards the use of GPUs clusters in HPC centers to accelerate particularly parallel codes as the ones related with the training of artificial neural networks. This paper presents a successful use case of a supercomputing facility, SCAYLE - Centro de Supercomputacion de Castilla y Leon -(Spain) by a group of robotic researchers while participating in an international robotics competition - the ERL Smart CIty RObotic Challenge (SciRoc). The goal of the paper is to show that HPC facilities can be required to provided particular SLAs (Service Level Agreement). In the case described, the HPC services were used to train neural networks for object recognition, that could not be easily trained on-site and that cannot be trained in advanced because of the regulation of the competition. |
| Databáze: | OpenAIRE |
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