Understanding Distributed Deep Learning Performance by Correlating HPC and Machine Learning Measurements

Author:

Veroneze Solórzano Ana LuisaORCID,Mello Schnorr LucasORCID

Publisher

Springer International Publishing

Reference31 articles.

1. Abadi, M., et al.: TensorFlow: large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467 (2016)

2. Abadi, M., et al.: TensorFlow: a system for large-scale machine learning. In: USENIX Symposium on Operating Systems Design and Implementation, OSDI 2016, pp. 265–283. USENIX Association (2016)

3. Ravikumar, A., Harini, S.: A comprehensive review and evaluation of distributed deep learning on cloud environments. J. Crit. Rev. 7(19), 9519–9538 (2020)

4. Cappello, F., et al.: Grid’5000: a large scale and highly reconfigurable grid experimental testbed. In: The 6th IEEE/ACM International Workshop on Grid Computing, pp. 8–pp. IEEE (2005)

5. Competence Center for HPC: Tarantella: distributed deep learning framework (2020). https://github.com/cc-hpc-itwm/tarantella

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Early Experiences of Noise-Sensitivity Performance Analysis of a Distributed Deep Learning Framework;2022 IEEE International Conference on Cluster Computing (CLUSTER);2022-09

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