Treffer: Distributed Machine Learning:Based on Computational resources available
Title:
Distributed Machine Learning:Based on Computational resources available
Publisher Information:
Zenodo
Publication Year:
2025
Collection:
Zenodo
Document Type:
Fachzeitschrift
article in journal/newspaper
Language:
unknown
Relation:
https://zenodo.org/records/15773425; oai:zenodo.org:15773425; https://doi.org/10.5281/zenodo.15773425
DOI:
10.5281/zenodo.15773425
Rights:
Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number:
edsbas.FF21DD64
Database:
BASE
Weitere Informationen
We propose a novel dynamic distributed training framework that applies distributed learning principles over a local area network (LAN). Each node in the network runs a unified Python-based agent (using Flask and PyTorch) and self-benchmarks its GPU performance using glmark2. The node with the lowest benchmark score is elected master, while others become workers.