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Fine-tuning Language Models over Slow Networks using Activation
  Compression with Guarantees

Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees

2 June 2022
Jue Wang
Binhang Yuan
Luka Rimanic
Yongjun He
Tri Dao
Beidi Chen
Christopher Ré
Ce Zhang
    AI4CE
ArXivPDFHTML

Papers citing "Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees"

9 / 9 papers shown
Title
COAT: Compressing Optimizer states and Activation for Memory-Efficient FP8 Training
COAT: Compressing Optimizer states and Activation for Memory-Efficient FP8 Training
Haocheng Xi
Han Cai
Ligeng Zhu
Y. Lu
Kurt Keutzer
Jianfei Chen
Song Han
MQ
68
9
0
25 Oct 2024
Scaling Expert Language Models with Unsupervised Domain Discovery
Scaling Expert Language Models with Unsupervised Domain Discovery
Suchin Gururangan
Margaret Li
M. Lewis
Weijia Shi
Tim Althoff
Noah A. Smith
Luke Zettlemoyer
MoE
22
46
0
24 Mar 2023
Does compressing activations help model parallel training?
Does compressing activations help model parallel training?
S. Bian
Dacheng Li
Hongyi Wang
Eric P. Xing
Shivaram Venkataraman
19
5
0
06 Jan 2023
RCD-SGD: Resource-Constrained Distributed SGD in Heterogeneous
  Environment via Submodular Partitioning
RCD-SGD: Resource-Constrained Distributed SGD in Heterogeneous Environment via Submodular Partitioning
Haoze He
Parijat Dube
15
1
0
02 Nov 2022
lo-fi: distributed fine-tuning without communication
lo-fi: distributed fine-tuning without communication
Mitchell Wortsman
Suchin Gururangan
Shen Li
Ali Farhadi
Ludwig Schmidt
Michael G. Rabbat
Ari S. Morcos
27
24
0
19 Oct 2022
ScaleCom: Scalable Sparsified Gradient Compression for
  Communication-Efficient Distributed Training
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
Chia-Yu Chen
Jiamin Ni
Songtao Lu
Xiaodong Cui
Pin-Yu Chen
...
Naigang Wang
Swagath Venkataramani
Vijayalakshmi Srinivasan
Wei Zhang
K. Gopalakrishnan
27
66
0
21 Apr 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference
  and training in neural networks
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler
Dan Alistarh
Tal Ben-Nun
Nikoli Dryden
Alexandra Peste
MQ
141
684
0
31 Jan 2021
An Efficient Statistical-based Gradient Compression Technique for
  Distributed Training Systems
An Efficient Statistical-based Gradient Compression Technique for Distributed Training Systems
A. Abdelmoniem
Ahmed Elzanaty
Mohamed-Slim Alouini
Marco Canini
49
74
0
26 Jan 2021
Megatron-LM: Training Multi-Billion Parameter Language Models Using
  Model Parallelism
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
M. Shoeybi
M. Patwary
Raul Puri
P. LeGresley
Jared Casper
Bryan Catanzaro
MoE
245
1,817
0
17 Sep 2019
1