Computing platforms in autonomous vehicles record large amounts of data from many sensors,
process the data through machine learning models, and make decisions to ensure the vehicle\'s safe
operation. Fast, accurate, and reliable decision-making is critical. Traditional computer processors lack the
power and flexibility needed for the perception and machine vision demands of advanced autonomous
driving tasks. Hardware accelerators are special-purpose coprocessors that help autonomous vehicles meet
performance requirements for higher levels of autonomy. This paper provides an overview of ML
accelerators with examples of their use for machine vision in autonomous vehicles. We offer
recommendations for researchers and practitioners and highlight a trajectory for ongoing and future
research in this emerging field.
自主驾驶中的硬件加速器
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