Hy-Fi: Hybrid Five-Dimensional Parallel DNN Training on High-Performance GPU Clusters-Reference-Cited by-同舟云学术

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Hy-Fi: Hybrid Five-Dimensional Parallel DNN Training on High-Performance GPU Clusters

Published:2022 Issue: Volume: Page:109-130
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Jain Arpan,Shafi Aamir,Anthony Quentin,Kousha Pouya,Subramoni Hari,Panda Dhableswar K.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-07312-0_6

Reference25 articles.

1. Awan, A.A., Hamidouche, K., Hashmi, J.M., Panda, D.K.: S-Caffe: co-designing MPI runtimes and Caffe for scalable deep learning on modern GPU clusters. In: Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, pp. 193–205. ACM, New York (2017)

2. Awan, A.A., Jain, A., Anthony, Q., Subramoni, H., Panda, D.K.: HyPar-Flow: exploiting MPI and Keras for scalable hybrid-parallel DNN training using TensorFlow (2019)

3. Awan, A.A., Subramoni, H., Panda, D.K.: An in-depth performance characterization of CPU- and GPU-based DNN training on modern architectures. In: Proceedings of the Machine Learning on HPC Environments, MLHPC 2017, pp. 8:1–8:8. ACM, New York (2017)

4. Bauer, M., Treichler, S., Slaughter, E., Aiken, A.: Legion: expressing locality and independence with logical regions. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC 2012. IEEE Computer Society Press (2012)

5. Ben-Nun, T., Hoefler, T.: Demystifying parallel and distributed deep learning: an in-depth concurrency analysis. CoRR abs/1802.09941 (2018)

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3. ScaMP: Scalable Meta-Parallelism for Deep Learning Search;2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid);2023-05

4. AccDP: Accelerated Data-Parallel Distributed DNN Training for Modern GPU-Based HPC Clusters;2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC);2022-12

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