Decode the Workload: Training Deep Learning Models for Efficient Compute Cluster Representation
- DOI
- 10.1051/epjconf/202533701120
- Published
- 2025
- Container
- EPJ Web of Conferences
- Publisher
- EDP Sciences
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1051/epjconf/202533701120,
title = {Decode the Workload: Training Deep Learning Models for Efficient Compute Cluster Representation},
author = {Ahmed Hossam Mohammed and Mark Jones and Diana McSpadden and Malachi Schram and Bryan Hess and Kishansingh Rajput},
year = {2025},
journal = {EPJ Web of Conferences},
doi = {10.1051/epjconf/202533701120},
url = {https://doi.org/10.1051/epjconf/202533701120}
}RIS
TY - JOUR TI - Decode the Workload: Training Deep Learning Models for Efficient Compute Cluster Representation AU - Ahmed Hossam Mohammed AU - Mark Jones AU - Diana McSpadden AU - Malachi Schram AU - Bryan Hess AU - Kishansingh Rajput PY - 2025 JO - EPJ Web of Conferences DO - 10.1051/epjconf/202533701120 UR - https://doi.org/10.1051/epjconf/202533701120 ER -
APA
Mohammed, A. H., Jones, M., McSpadden, D., Schram, M., Hess, B., & Rajput, K. (2025). Decode the Workload: Training Deep Learning Models for Efficient Compute Cluster Representation. EPJ Web of Conferences. https://doi.org/10.1051/epjconf/202533701120
Source records
- crossref · retrieved 2026-09-25T16:37:12.763Z