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Designing transformer oil immersion cooling servers for machine learning and first principle calculations.

Authors :
Takahashi, Keisuke
Miyazato, Itsuki
Maeda, Satoshi
Takahashi, Lauren
Source :
PLoS ONE. 5/17/2022, Vol. 17 Issue 5, p1-7. 7p.
Publication Year :
2022

Abstract

A transfomer oil immersion cooling server is designed and constructed for machine learning applications and first principle calculations that are carried out for materials-related research. CPU, motherboard, random access memory, hard disk drive, solid state drive, graphic card, and the power supply unit are submerged into the transformer oil in order to cool the entire system. Benchmark tests reveal that overall performance is improved while performance times for multicore calculations are dramatically improved. Furthermore, calculation times for machine learning with large data sets and density functional theory calculations are shortened during single core calculations. Thus, a transformer oil immersion cooling server is proposed to be an alternative cooling system used for improving the performance of first principle calculations and machine learning. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
17
Issue :
5
Database :
Academic Search Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
156917001
Full Text :
https://doi.org/10.1371/journal.pone.0266880