BOAD: Optimizing Distributed Communication with In-Kernel Broadcast and Aggregation

Author:

Su Jianchang1ORCID,Zhang Yifan1ORCID,Huang Linpu1ORCID,Zhang Wei1ORCID

Affiliation:

1. University of Connecticut, Storrs, CT, USA

Publisher

ACM

Reference32 articles.

1. Martín Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dandelion Mané Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Viégas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https://www.tensorflow.org/ Software available from tensorflow.org.

2. K. A. Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth. 2016. Practical Secure Aggregation for Federated Learning on User-Held Data. In NIPS Workshop on Private Multi-Party Machine Learning. https://arxiv.org/abs/1611.04482

3. Understanding host network stack overheads

4. SPEED: Resource-Efficient and High-Performance Deployment for Data Plane Programs

5. Toward Low-Overhead Inter-Switch Coordination in Network-Wide Data Plane Program Deployment

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