Fast and Low-Power Quantized Fixed Posit High-Accuracy DNN Implementation

Sumit Walia,Bachu Varun Tej,Arpita Kabra,Joydeep Devnath,Joycee Mekie

IEEE Transactions on Very Large Scale Integration (VLSI) Systems（2022）

Cited 5|Views4

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Abstract

This brief compares quantized float-point representation in posit and fixed-posit formats for a wide variety of pre-trained deep neural networks (DNNs). We observe that fixed-posit representation is far more suitable for DNNs as it results in a faster and low-power computation circuit. We show that accuracy remains within the range of 0.3% and 0.57% of top-1 accuracy for posit and fixed-posit quan...

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Key words

Quantization (signal),Standards,Dynamic range,Very large scale integration,Program processors,Deep learning,Convolutional neural networks

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