Optimizing Distributed Training on Frontier for Large Language Models

Author:

Dash Sajal1,Lyngaas Isaac R1,Yin Junqi1,Wang Xiao1,Egele Romain2,Ellis J. Austin3,Maiterth Matthias1,Cong Guojing1,Wang Feiyi1,Balaprakash Prasanna1

Affiliation:

1. Oak Ridge National Laboratory

2. Université Paris-Saclay

3. AMD

Funder

U.S. Department of Energy

Publisher

IEEE

Reference27 articles.

1. Scaling laws for neural language models;Kaplan;arXiv preprint,2020

2. Language models are few-shot learners;Brown;Advances in neural information processing systems,2020

3. Bloom: A 176b-parameter open-access multilingual language model;Workshop;arXiv preprint,2022

4. Opt: Open pre-trained transformer language models;Zhang;arXiv preprint,2022

5. Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model;Smith;arXiv preprint,2022

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1. A Review on Neuro-symbolic AI Improvements to Natural Language Processing;2024 47th MIPRO ICT and Electronics Convention (MIPRO);2024-05-20

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