Paper

CascadeCNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks

This work presents CascadeCNN, an automated toolflow that pushes the quantisation limits of any given CNN model, aiming to perform high-throughput inference. A two-stage architecture tailored for any given CNN-FPGA pair is generated, consisting of a low- and high-precision unit in a cascade... (read more)

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