Summary
The intricate dynamics of fluid interfaces, disordered liquid-liquid emulsions, and soft microfluidic droplet crystals, collectively known
as soft glass materials (SGM), pose challenges to non-equilibrium thermodynamics and hold profound implications for engineering
applications such as combustion, materials design, and food processing. Advances in SGM modeling within the ERC COPMAT project
offer opportunities for innovative mesoscale materials in fields like tissue engineering, photonics, and catalysis.
The Lightweight Lattice Boltzmann (LB) scheme, which relies on hydrodynamic moments, models SGM by preventing droplet
coalescence including near-contact interactions (NCI) due to surfactants. Integrated into LBcuda, an open-source software optimized
for GPUs, it efficiently simulates complex flows while saving electrical energy, in line with the goals of the European Green Deal.
The LBFAST project aims to optimize LBcuda's implementation for HPC clusters powered by GPUs, achieving processing rates of
several hundred GLUPS while using only 50% of computational resources, resulting in a 75% reduction in energy costs compared to
standard LB methods. This enhancement enables accelerated production rates for industrial applications and aligns with the criteria
of the EuroHPC Joint Undertaking, benefiting users addressing energy and environmental challenges in the next exascale computing
generation.
as soft glass materials (SGM), pose challenges to non-equilibrium thermodynamics and hold profound implications for engineering
applications such as combustion, materials design, and food processing. Advances in SGM modeling within the ERC COPMAT project
offer opportunities for innovative mesoscale materials in fields like tissue engineering, photonics, and catalysis.
The Lightweight Lattice Boltzmann (LB) scheme, which relies on hydrodynamic moments, models SGM by preventing droplet
coalescence including near-contact interactions (NCI) due to surfactants. Integrated into LBcuda, an open-source software optimized
for GPUs, it efficiently simulates complex flows while saving electrical energy, in line with the goals of the European Green Deal.
The LBFAST project aims to optimize LBcuda's implementation for HPC clusters powered by GPUs, achieving processing rates of
several hundred GLUPS while using only 50% of computational resources, resulting in a 75% reduction in energy costs compared to
standard LB methods. This enhancement enables accelerated production rates for industrial applications and aligns with the criteria
of the EuroHPC Joint Undertaking, benefiting users addressing energy and environmental challenges in the next exascale computing
generation.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101187935 |
| Start date: | 01-12-2024 |
| End date: | 31-05-2026 |
| Total budget - Public funding: | - 150 000,00 Euro |
Cordis data
Original description
The intricate dynamics of fluid interfaces, disordered liquid-liquid emulsions, and soft microfluidic droplet crystals, collectively knownas soft glass materials (SGM), pose challenges to non-equilibrium thermodynamics and hold profound implications for engineering
applications such as combustion, materials design, and food processing. Advances in SGM modeling within the ERC COPMAT project
offer opportunities for innovative mesoscale materials in fields like tissue engineering, photonics, and catalysis.
The Lightweight Lattice Boltzmann (LB) scheme, which relies on hydrodynamic moments, models SGM by preventing droplet
coalescence including near-contact interactions (NCI) due to surfactants. Integrated into LBcuda, an open-source software optimized
for GPUs, it efficiently simulates complex flows while saving electrical energy, in line with the goals of the European Green Deal.
The LBFAST project aims to optimize LBcuda's implementation for HPC clusters powered by GPUs, achieving processing rates of
several hundred GLUPS while using only 50% of computational resources, resulting in a 75% reduction in energy costs compared to
standard LB methods. This enhancement enables accelerated production rates for industrial applications and aligns with the criteria
of the EuroHPC Joint Undertaking, benefiting users addressing energy and environmental challenges in the next exascale computing
generation.
Status
SIGNEDCall topic
ERC-2024-POCUpdate Date
21-11-2024
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