all AI news
F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization. (arXiv:2202.05239v1 [cs.CV])
Feb. 11, 2022, 2:11 a.m. | Qing Jin, Jian Ren, Richard Zhuang, Sumant Hanumante, Zhengang Li, Zhiyu Chen, Yanzhi Wang, Kaiyuan Yang, Sergey Tulyakov
cs.LG updates on arXiv.org arxiv.org
Neural network quantization is a promising compression technique to reduce
memory footprint and save energy consumption, potentially leading to real-time
inference. However, there is a performance gap between quantized and
full-precision models. To reduce it, existing quantization approaches require
high-precision INT32 or full-precision multiplication during inference for
scaling or dequantization. This introduces a noticeable cost in terms of
memory, speed, and required energy. To tackle these issues, we present F8Net, a
novel quantization framework consisting of only fixed-point 8-bit
multiplication. …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Senior Software Engineer, Generative AI (C++)
@ SoundHound Inc. | Toronto, Canada