ERC Starting Grant · 2018
Re-thinking Efficiency in Deep Learning under Accelerators and commodity and processors
In just a few short years, breakthroughs from the field of deep learning have transformed how computers perform a wide-variety of tasks such as recognizing a face, driving a car or translating a language. Not only has deep learning become an everyday tool, it is also the most promising direction for tackling a number of still open problems in machine learning and artificial intelligence. However, routine deep learning activities (such as training a model) exert severe resource demands (e.g., memory, compute, energy) that are currently slowing the advancement of the field, and preventing full global participation in this research to only the largest of companies. The goal of REDIAL is to…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.