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The Environmental Cost of Bioinformatics at GenOuest

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Bibliographic Details
Title: The Environmental Cost of Bioinformatics at GenOuest
Authors: Siminel, Rémy, Robin, Stéphanie, Le Deun, Erell, Boudet, Matéo, Bretaudeau, Anthony
Contributors: Siminel, Rémy
Publisher Information: 2025.
Publication Year: 2025
Subject Terms: Energy efficiency, High-performance computing HPC, Sustainable computing, Carbon footprint, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Description: Background: Bioinformatics heavily depends on high-performance computing (HPC), whichconsumes a large amount of energy and significantly impacts the environment. As datasets expandand analytical tools grow more complex - especially with the rise of AI-driven methods - thecarbon footprint of computational research increases, making sustainable solutions essential.Results: In order to reduce the environmental impact of our bioinformatics research, our approachis to first accurately measure real-time energy use and then define a consumption optimizationstrategy. We track overall power consumption and break it down by team, project and user, whichwill allow us to give users quantitative feedback on the energy and equivalent carbon emissioncosts of their computations and data storage. Raising user awareness is crucial as behavioralchanges, like reducing redundant computations, can significantly lower overall energy use.Providing these carbon footprints fosters a culture of sustainability in computational research anddrives a shift toward more environmentally conscious computational practices. GenOuest hasalready integrated dynamic power management, scaling resources based on the day/night cycle,with potential for further refinement. All this fits within the larger movement to quantify theenvironmental costs of research, like what’s done within the EcoInfo [1] or Labo 1.5 [2] initiatives.Conclusions: Real-time energy monitoring and user feedback could effectively reduce GenOuest’senvironmental impact, as increasing awareness and optimizing resource management are key tocreating a sustainable computational research environment.
Document Type: Conference object
File Description: application/pdf
Language: English
Access URL: https://hal.science/hal-05174309v1
Rights: CC BY
Accession Number: edsair.dedup.wf.002..e9e7e116519e256ba907bc41e49b9b32
Database: OpenAIRE
Description
Abstract:Background: Bioinformatics heavily depends on high-performance computing (HPC), whichconsumes a large amount of energy and significantly impacts the environment. As datasets expandand analytical tools grow more complex - especially with the rise of AI-driven methods - thecarbon footprint of computational research increases, making sustainable solutions essential.Results: In order to reduce the environmental impact of our bioinformatics research, our approachis to first accurately measure real-time energy use and then define a consumption optimizationstrategy. We track overall power consumption and break it down by team, project and user, whichwill allow us to give users quantitative feedback on the energy and equivalent carbon emissioncosts of their computations and data storage. Raising user awareness is crucial as behavioralchanges, like reducing redundant computations, can significantly lower overall energy use.Providing these carbon footprints fosters a culture of sustainability in computational research anddrives a shift toward more environmentally conscious computational practices. GenOuest hasalready integrated dynamic power management, scaling resources based on the day/night cycle,with potential for further refinement. All this fits within the larger movement to quantify theenvironmental costs of research, like what’s done within the EcoInfo [1] or Labo 1.5 [2] initiatives.Conclusions: Real-time energy monitoring and user feedback could effectively reduce GenOuest’senvironmental impact, as increasing awareness and optimizing resource management are key tocreating a sustainable computational research environment.