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000831669 001__ 831669
000831669 005__ 20230211043212.0
000831669 0247_ $$2CORDIS$$aG:(EU-Grant)951733$$d951733
000831669 0247_ $$2CORDIS$$aG:(EU-Call)H2020-INFRAEDI-2019-1$$dH2020-INFRAEDI-2019-1
000831669 0247_ $$2originalID$$acorda__h2020::951733
000831669 035__ $$aG:(EU-Grant)951733
000831669 150__ $$aResearch on AI- and Simulation-Based Engineering at Exascale$$y2021-01-01 - 2023-12-31
000831669 372__ $$aH2020-INFRAEDI-2019-1$$s2021-01-01$$t2023-12-31
000831669 450__ $$aRAISE$$wd$$y2021-01-01 - 2023-12-31
000831669 5101_ $$0I:(DE-588b)5098525-5$$2CORDIS$$aEuropean Union
000831669 680__ $$aCompute- and data-driven research encompasses a broad spectrum of disciplines and is the key to Europe’s global success in various scientific and economic fields. The massive amount of data produced by such technologies demands novel methods to post-process, analyze, and to reveal valuable mechanisms. The development of artificial intelligence (AI) methods is rapidly proceeding and they are progressively applied to many stages of workflows to solve complex problems. Analyzing and processing big data require high computational power and scalable AI solutions. Therefore, it becomes mandatory to develop entirely new  workflows from current applications that efficiently run on future high-performance computing architectures at Exascale. The Center of Excellence for Research on AI- and Simulation-based Engineering at Exascale (RAISE) will be the excellent enabler for the advancement of such technologies in Europe on industrial and academic levels, and a driver for novel intertwined AI and HPC methods. These technologies will be advanced along representative use-cases, covering a wide spectrum of academic and industrial applications, e.g., coming from wind energy harvesting, wetting hydrodynamics, manufacturing, physics, turbomachinery, and aerospace. It aims at closing the gap in full loops using forward simulation models and AI-based inverse inference models, in conjunction with statistical methods to learn from current and historical data. In this context, novel hardware technologies, i.e., Modular Supercomputing Architectures, Quantum Annealing, and prototypes from the DEEP project series will be used for exploring unseen performance in data processing. Best practices, support, and education for industry, SMEs, academia, and HPC centers on Tier-2 level and below will be developed and provided in RAISE's European network attracting new user communities. This goes along with the development of a business providing new services to various user communities.
000831669 909CO $$ooai:juser.fz-juelich.de:899715$$pauthority$$pauthority:GRANT
000831669 909CO $$ooai:juser.fz-juelich.de:899715
000831669 980__ $$aG
000831669 980__ $$aCORDIS
000831669 980__ $$aAUTHORITY