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@INPROCEEDINGS{John:1007707,
author = {John, Chelsea Maria and Ebert, Jan and Penke, Carolin and
Kesselheim, Stefan and Herten, Andreas},
title = {{O}pen{GPT}-{X} – {T}raining {L}arge {L}anguage {M}odels
on {HPC} {S}ystems},
reportid = {FZJ-2023-02173},
year = {2023},
abstract = {OpenGPT-X is a German initiative to build and train large
language models (LLMs). The project aims at providing an
open alternative to LLMs which are up to now private
property, along with a platform for researching methods to
train multilingual LLMs efficiently. For that, the project
not only utilizes the state-of-the-art in training models
but also incorporates new methods, algorithms, and tools.
Models trained within the project will be published and used
for pilot language services by industry partners. In
addition, further applications are expected through Gaia-X
federation. LLMs can scale to more than 175 Billion
parameters, which requires efficient usage of supercomputers
like JUWELS Booster. Especially in the light of the recent
successes of ChatGPT, our work clearly indicates that the
infrastructure of supercomputing centres and initiatives
aiming to provide resources to the public can have a large
societal impact. This poster outlines the initial progress
and future work of the project from Jülich Supercomputing
Center (JSC).},
month = {May},
date = {2023-05-21},
organization = {ISC High Performance 2023, Hamburg
(Germany), 21 May 2023 - 25 May 2023},
subtyp = {After Call},
keywords = {HPC (Other) / GPU (Other) / OpenGPTX (Other)},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / 5121 - Supercomputing $\&$
Big Data Facilities (POF4-512) / ATML-X-DEV - ATML
Accelerating Devices (ATML-X-DEV)},
pid = {G:(DE-HGF)POF4-5112 / G:(DE-HGF)POF4-5121 /
G:(DE-Juel-1)ATML-X-DEV},
typ = {PUB:(DE-HGF)24},
doi = {10.34732/XDVBLG-SVNDMJ},
url = {https://juser.fz-juelich.de/record/1007707},
}