Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning
- DOI
- 10.1109/ipdps53621.2022.00109
- Published
- 2022-05
- Container
- 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
- Publisher
- IEEE
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/ipdps53621.2022.00109,
title = {Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning},
author = {Truong Thao Nguyen and Francois Trahay and Jens Domke and Aleksandr Drozd and Emil Vatai and Jianwei Liao and Mohamed Wahib and Balazs Gerofi},
year = {2022},
journal = {2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)},
doi = {10.1109/ipdps53621.2022.00109},
url = {https://doi.org/10.1109/ipdps53621.2022.00109}
}RIS
TY - JOUR TI - Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning AU - Truong Thao Nguyen AU - Francois Trahay AU - Jens Domke AU - Aleksandr Drozd AU - Emil Vatai AU - Jianwei Liao AU - Mohamed Wahib AU - Balazs Gerofi PY - 2022 JO - 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS) DO - 10.1109/ipdps53621.2022.00109 UR - https://doi.org/10.1109/ipdps53621.2022.00109 ER -
APA
Nguyen, T. T., Trahay, F., Domke, J., Drozd, A., Vatai, E., Liao, J., Wahib, M., & Gerofi, B. (2022). Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning. 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS). https://doi.org/10.1109/ipdps53621.2022.00109
Source records
- crossref · retrieved 2026-09-27T15:57:10.331Z