4.6-Bit Quantization for Fast and Accurate Neural Network Inference on CPUs
Anton Trusov,
Elena Limonova,
Dmitry Nikolaev
et al.
Abstract:Quantization is a widespread method for reducing the inference time of neural networks on mobile Central Processing Units (CPUs). Eight-bit quantized networks demonstrate similarly high quality as full precision models and perfectly fit the hardware architecture with one-byte coefficients and thirty-two-bit dot product accumulators. Lower precision quantizations usually suffer from noticeable quality loss and require specific computational algorithms to outperform eight-bit quantization. In this paper, we prop… Show more
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