Green-IN Machine Learning at a Glance
María Elena Gutiérrez, Ma Ángeles Moraga, Félix García, Coral Calero
Abstract
The use of machine learning (ML) algorithms has an environmental impact to be fully considered. This article presents a green-in-driven approach to the development of ML models. The aim thereof is to meet operational requirements while ensuring a suitable tradeoff between performance/reliability and energy consumption.
Topics & Concepts
Computer scienceGreen computingEnergy consumptionReliability (semiconductor)Machine learningArtificial intelligenceRisk analysis (engineering)Cloud computingOperating systemPower (physics)Quantum mechanicsEcologyMedicineBiologyPhysicsGreen IT and SustainabilityEnergy Efficiency and ManagementMobile Crowdsensing and Crowdsourcing