Jumping Shift: A Logarithmic Quantization Method for Low-Power CNN Acceleration

Logarithmic quantization for Convolutional Neural Networks (CNN): a) fits well typical weights and activation distributions, and b) allows the replacement of the multiplication operation by a shift operation that can be implemented with fewer hardware resources. We propose a new quantization method named Jumping Log Quantization (JLQ). The key...

A New Logarithmic Quantization Technique and Corresponding Processing Element Design for CNN Accelerators

Convolutional Neural Networks (CNN) have become a popular solution for computer vision problems. However, due to the high data volumes and intensive computation involved in CNNs, deploying CNNs on low-power hardware systems is still challenging.<br/>The power consumption of CNNs can be prohibitive in the most common implementation platforms:...