The research paper “Auto-tuning Multi-GPU High-Fidelity Numerical Simulations for Urban Air Mobility” from RefMap partners, Kungliga Tekniska Hoegskolan (KTH) and Institute of Communication and Computer Systems (ICCS) was presented at the recent DATE 2024 conference, Design, Automation, and Test in Europe Conference. Namely, Manolis Katsaragakis researcher at ICCS has presented the work in the “Multi-Partner Projects” session.
The paper outlines the first promising results of RefMap's strategy to optimise high-fidelity numerical simulations for UAM using GPU acceleration capabilities and autotuning techniques.
The theme of the paper is based on the following topic: the aviation field is rapidly evolving towards an era where both typical aviation and Unmanned Aircraft Systems are essential and co-exist in the same airspace. This new territory raises important concerns regarding environmental impact, safety, and societal acceptance. The RefMap European Project is an initiative that addresses these issues and aims at optimising air traffic in terms of the environmental footprint in aviation and drone flights. One of RefMap's objectives is the development of powerful deep-learning models that predict urban flow based on extensive CFD simulations. The excessive time requirements of CFD simulations require the computational power of exascale heterogeneous supercomputer clusters.
The paper was drafted by K. Koliogeorgi, G. Anagnostopoulos, G. Zampino, M. Sanchis, R. Vinuesa, and S. Xydis. Read another relevant article on our website here.
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