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NCC Finland
NCC Finland is part of the EuroCC2 project, which establishes national HPC competence centers in different European countries. NCC Finland's mission is to support and improve the capabilities of Finnish business users to utilize the opportunities of high- performance computing, data analytics and artificial intelligence.Through EuroCC Finland, companies have access to the computing capacity of the EuroHPC LUMI Supercomputer. EuroCC Finland is operated by the CSC – IT Center for Science.
Industrial organisations involved:
The AI TRANSPWOOD EU project focuses on transparent wood-based materials and their modelling. The project aims to effectively integrate advanced AI-based computational models with SSbD (Safe and Sustainable by Design) principles for the safe and sustainable design of wood-based composites. From Finland, VTT, which is coordinating the project, and Aalto University are participating in this 13-partner project.
Technical/scientific Challenge:
The role of VTT and Aalto in the project focuses on the development of AI-based surrogate models, i.e., lighter AI models that replace the original model, as well as the broad development of various machine learning methods,” says Professor Simo Särkkä
Solution:
The AI-TRANSPWOOD project utilizes the GPU units of the LUMI supercomputer to develop surrogate AI models and physics-driven AI models. They are trained using neural network models and PyTorch software to recognize different properties of wood and screen them for the most promising candidates for new materials.
"Lightweight AI-based surrogate models are used for optimization instead of slow and heavy physics-based models, for example. This significantly speeds uup model development," explains Aalto researcher Dr. Marcin Minkowski.
Business impact:
The most promising surrogate models can be selected for development as AI models, and lighter models can be scaled up massively, for example, in a supercomputer computing environment. This is currently an established method for optimising and discovering new materials. If the original computational model is unsuitable for a high-performance computing environment, a surrogate model can also be used in this case," explains Joonas Linnosmaa, Senior AI Researcher at VTT.
Benefits:
* computing power and scalability in AI model development
* VTT researchers are generally aware of and trained in the use of CSC and LUMI resources
* Easy access to resources
* Accelerated material development process
Success story # Highlights:
* Keywords: HPC, material science, wood, AI model, surrogate AI model
* Industry Sector Research and industry
* Technology EuroHPC LUMI, neural network models and PyTorch software
Contact:
NCC Finland : Development manager Dan Still, CSC, dan.still@csc.fi/
Customer manager Tiina Leiponen, tiina.leiponen@csc.fi