Abstract: To build Neural Networks (NNs) on edge devices, Binarized Neural Network (BNN) has been proposed on the software side, while Computing-in-Memory (CiM) architecture has been proposed on the ...
Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...
If you’ve vowed to start strength training but can’t seem to make a routine stick, you’re not alone. Nathaniel Serrurier, CSCS, a personal trainer and doctoral student at Columbia University’s RunLab, ...
Abstract: This paper presents a Posit-based Mixed Precision (PMP) framework for deep neural network (DNN) training and inference, leveraging Posit32, Posit16, and Posit8 across different computational ...
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