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Optimization of Collective Reduction Operations
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Cited by
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Goyal, P., Dollár, P., Girshick, R., Noordhuis, P., Wesolowski, L., Kyrola, A., Tulloch, A., Jia, Y., & He, K. (2017) · arXiv · doi:10.48550/arxiv.1706.02677 · Cited by 2,294
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
Lin, Y., Han, S., Mao, H., Wang, Y., & Dally, W. J. (2017) · arXiv · doi:10.48550/arxiv.1712.01887 · Cited by 1,134
Demystifying Parallel and Distributed Deep Learning: An In-depth Concurrency Analysis
Ben-Nun, T., & Hoefler, T. (2020) · ACM Computing Surveys · doi:10.1145/3320060 · Cited by 577
You, Y., Zhang, Z., Hsieh, C.-J., Demmel, J., & Keutzer, K. (2018) · Proceedings of the 47th International Conference on Parallel Processing · doi:10.1145/3225058.3225069 · Cited by 384
Taming unbalanced training workloads in deep learning with partial collective operations
Li, S., Ben-Nun, T., Girolamo, S. D., Alistarh, D., & Hoefler, T. (2020) · Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming · doi:10.1145/3332466.3374528 · Cited by 57
Metadata
- Authors
- Rabenseifner, R.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2004
- Pages
- 1-9
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1572016165
- Cited by
- 185
- References
- 0
- FWCI
- 2.82
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Optimization of Collective Reduction Operations. https://app.cochat.ai/papers/10.1007/978-3-540-24685-5_1
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- Rabenseifner, R. (2004). Optimization of Collective Reduction Operations. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-540-24685-5_1
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.