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A Linear Algebraic Approach to Model Parallelism in Deep Learning

A Linear Algebraic Approach to Model Parallelism in Deep Learning

4 June 2020
Russell J. Hewett
Thomas J. Grady
    FedML
ArXivPDFHTML

Papers citing "A Linear Algebraic Approach to Model Parallelism in Deep Learning"

2 / 2 papers shown
Title
Learned multiphysics inversion with differentiable programming and
  machine learning
Learned multiphysics inversion with differentiable programming and machine learning
M. Louboutin
Ziyi Yin
Rafael Orozco
Thomas J. Grady
Ali Siahkoohi
G. Rizzuti
Philipp A. Witte
O. Møyner
Gerard Gorman
Felix J. Herrmann
AI4CE
26
10
0
12 Apr 2023
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
1,821
0
17 Sep 2019
1