Table-Based Neural Units: Fully Quantizing Networks for Multiply-Free Inference

11 Jun 2019Michele CovellDavid MarwoodShumeet BalujaNick Johnston

In this work, we propose to quantize all parts of standard classification networks and replace the activation-weight--multiply step with a simple table-based lookup. This approach results in networks that are free of floating-point operations and free of multiplications, suitable for direct FPGA and ASIC implementations... (read more)

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