FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding

28 October 2021

Papers citing "FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding"

6 / 6 papers shown

Title
On Stochastic Rounding with Few Random Bits Andrew Fitzgibbon Stephen Felix 30 0 0 29 Apr 2025
GSQ-Tuning: Group-Shared Exponents Integer in Fully Quantized Training for LLMs On-Device Fine-tuning Sifan Zhou Shuo Wang Zhihang Yuan Mingjia Shi Yuzhang Shang Dawei Yang ALM MQ 90 0 0 18 Feb 2025
Effective Interplay between Sparsity and Quantization: From Theory to Practice Simla Burcu Harma Ayan Chakraborty Elizaveta Kostenok Danila Mishin Dongho Ha ... Martin Jaggi Ming Liu Yunho Oh Suvinay Subramanian Amir Yazdanbakhsh MQ 44 6 0 31 May 2024
DAISM: Digital Approximate In-SRAM Multiplier-based Accelerator for DNN Training and Inference Lorenzo Sonnino Shaswot Shresthamali Yuan He Masaaki Kondo 14 1 0 12 May 2023
With Shared Microexponents, A Little Shifting Goes a Long Way Bita Darvish Rouhani Ritchie Zhao V. Elango Rasoul Shafipour Mathew Hall ... Eric S. Chung Zhaoxia Deng S. Naghshineh Jongsoo Park Maxim Naumov MQ 43 38 0 16 Feb 2023
FlexBlock: A Flexible DNN Training Accelerator with Multi-Mode Block Floating Point Support Seock-Hwan Noh Jahyun Koo Seunghyun Lee Jongse Park Jaeha Kung AI4CE 32 17 0 13 Mar 2022