Summary
Artificial-Intelligence-Augmented Cooling System for Small Data Centres “ECO-Qube”; is a holistic management system which aims to enhance energy efficiency and cooling performance by orchestrating both hardware and software components in edge computing applications.
ECO-Qube is a data driven approach which utilizes valuable unused data from active data centre components. Created big data is being used by an artificial intelligence augmented system which detects cooling and energy requirements instantaneously.
ECO-Qube differentiates from conventional cooling systems which keep operating temperatures within a strict interval and do not evaluate measurable cooling performance. Unmeasured cooling performance leads underperformed airflow, thermal disequilibrium, and high energy consumption. On the contrary, ECO-Qube offers a zonal heat management system which benefits from Computational Fluid Dynamics (CFD) simulations to adapt cooling system for the best airflow and cooling performance with minimum energy consumption. Moreover, ECO-Qube realizes smart workload orchestration to keep the CPUs at their most energy efficient state and maintain the thermal equilibrium to reduce overheating risk.
Sustainability is another priority for ECO-Qube’s smart energy management system (EMS), which is designed to track the energy demand and operate the energy supply in cooperation with building/district’s EMS. This synergy maximizes the energy supplied from renewable energy sources and minimizes the energy supplied from sources with big carbon footprint.
ECO-Qube solution will be assessed in three different pilots from different climatic conditions to validate energy efficiency under different external variables.
ECO-Qube is a data driven approach which utilizes valuable unused data from active data centre components. Created big data is being used by an artificial intelligence augmented system which detects cooling and energy requirements instantaneously.
ECO-Qube differentiates from conventional cooling systems which keep operating temperatures within a strict interval and do not evaluate measurable cooling performance. Unmeasured cooling performance leads underperformed airflow, thermal disequilibrium, and high energy consumption. On the contrary, ECO-Qube offers a zonal heat management system which benefits from Computational Fluid Dynamics (CFD) simulations to adapt cooling system for the best airflow and cooling performance with minimum energy consumption. Moreover, ECO-Qube realizes smart workload orchestration to keep the CPUs at their most energy efficient state and maintain the thermal equilibrium to reduce overheating risk.
Sustainability is another priority for ECO-Qube’s smart energy management system (EMS), which is designed to track the energy demand and operate the energy supply in cooperation with building/district’s EMS. This synergy maximizes the energy supplied from renewable energy sources and minimizes the energy supplied from sources with big carbon footprint.
ECO-Qube solution will be assessed in three different pilots from different climatic conditions to validate energy efficiency under different external variables.
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| Web resources: | https://cordis.europa.eu/project/id/956059 |
| Start date: | 01-10-2020 |
| End date: | 30-09-2024 |
| Total budget - Public funding: | 3 677 870,00 Euro - 2 998 988,00 Euro |
Cordis data
Original description
Artificial-Intelligence-Augmented Cooling System for Small Data Centres “ECO-Qube”; is a holistic management system which aims to enhance energy efficiency and cooling performance by orchestrating both hardware and software components in edge computing applications.ECO-Qube is a data driven approach which utilizes valuable unused data from active data centre components. Created big data is being used by an artificial intelligence augmented system which detects cooling and energy requirements instantaneously.
ECO-Qube differentiates from conventional cooling systems which keep operating temperatures within a strict interval and do not evaluate measurable cooling performance. Unmeasured cooling performance leads underperformed airflow, thermal disequilibrium, and high energy consumption. On the contrary, ECO-Qube offers a zonal heat management system which benefits from Computational Fluid Dynamics (CFD) simulations to adapt cooling system for the best airflow and cooling performance with minimum energy consumption. Moreover, ECO-Qube realizes smart workload orchestration to keep the CPUs at their most energy efficient state and maintain the thermal equilibrium to reduce overheating risk.
Sustainability is another priority for ECO-Qube’s smart energy management system (EMS), which is designed to track the energy demand and operate the energy supply in cooperation with building/district’s EMS. This synergy maximizes the energy supplied from renewable energy sources and minimizes the energy supplied from sources with big carbon footprint.
ECO-Qube solution will be assessed in three different pilots from different climatic conditions to validate energy efficiency under different external variables.
Status
SIGNEDCall topic
LC-SC3-B4E-5-2020Update Date
26-10-2022
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Organisations
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| LANDE ENDUSTRIYEL METAL URUNLER SANAYI VE TICARET AS (Coördinator)
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| BITNET BILISIM HIZMETLERI LIMITED SIRKETI
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| BLOCKHEATING BV
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| ENDOKS ENEJI DAGITIM SISTEMLERI SANAYI ITHALAT VE IHRACAT LIMITED SIRKETI
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| GIROA SOCIEDAD ANONIMA
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| HELIO AG
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| LULEA TEKNISKA UNIVERSITET
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| R2M SOLUTION SPAIN SL
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| STICHTING GREEN IT CONSORTIUM REGIO AMSTERDAM
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| SUSTAINABLE DIGITAL INFRASTRUCTURE ALLIANCE EV
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| Swiss Federal Laboratories for Materials Science and Technology - EMPA
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| TASARIM SIMULASYON TEKNOLOJILERI SANAYI VE TICARET AS
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| VATTENFALL AB