S4: a High-sparsity, High-performance AI Accelerator

S4: a High-sparsity, High-performance AI Accelerator

16 July 2022

Dongkuan Xu

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Papers citing "S4: a High-sparsity, High-performance AI Accelerator"

8 / 8 papers shown

Title
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm Shaoyi Huang Dongkuan Xu Ian En-Hsu Yen Yijue Wang Sung-En Chang ... Shiyang Chen Mimi Xie Sanguthevar Rajasekaran Hang Liu Caiwen Ding CLL VLM 42 32 0 15 Oct 2021
I-BERT: Integer-only BERT Quantization Sehoon Kim A. Gholami Z. Yao Michael W. Mahoney Kurt Keutzer MQ 144 351 0 05 Jan 2021
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers Wenhui Wang Furu Wei Li Dong Hangbo Bao Nan Yang Ming Zhou VLM 150 1,267 0 25 Feb 2020
TinyBERT: Distilling BERT for Natural Language Understanding Xiaoqi Jiao Yichun Yin Lifeng Shang Xin Jiang Xiao Chen Linlin Li F. Wang Qun Liu VLM 105 1,860 0 23 Sep 2019
The State of Sparsity in Deep Neural Networks Trevor Gale Erich Elsen Sara Hooker 161 758 0 25 Feb 2019
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 235 3,473 0 09 Mar 2018
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 194 1,276 0 05 Oct 2017
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 259 8,842 0 01 Oct 2015