Speakers
Description
In recent years, research in the space community has shown a growing interest in AI, mostly driven by systems miniaturization and commercial competition. FPGA have proven to be competitive accelerators for these algorithms and works proposing methods for automating the design on these devices have acquired relevance. The common purpose is to enable a wide range of users without specific skills to accelerate AI models on FPGA with reduced development times.This presentation will focus on the characterization of FPG-AI, a novel technology-independent toolflow for automating AI deployment on FPGA, on NanoXplore devices. We will present preliminary information on the achieved performances in terms of computational power and resource consumption on a representative use case scenario.
