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We review the problem of automating hardware-aware architectural design process of Deep Neural Networks (DNNs). The field of Convolutional Neural Network (CNN) algorithm design has led to advancements in many fields such as computer vision, virtual reality, and autonomous driving. The end-to-end design process of a CNN is a challenging and time-consuming task as it requires expertise in multiple areas such as signal and image processing, neural networks, and optimization. At the same time,doi:10.1145/3524500 fatcat:4ibnwmgbdnbhjpk4u7soc6aom4