Which can Accelerate Distributed Machine Learning Faster: Hybrid Optical/Electrical or Optical Reconfigurable DCN?-Reference-Cited by-同舟云学术

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Which can Accelerate Distributed Machine Learning Faster: Hybrid Optical/Electrical or Optical Reconfigurable DCN?

Published:2022 Issue: Volume: Page:
ISSN:
Container-title:Optical Fiber Communication Conference (OFC) 2022
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Author:

Yang Hao,Zhu Zuqing,Proietti Roberto,Ben Yoo S. J.

Abstract

We run various distributed machine learning (DML) architectures in a hybrid optical/electrical DCN and an optical DCN based on Hyper-FleX-LION. Experimental results show that Hyper-FleX-LION gains faster DML acceleration and improves acceleration ratio by up to 22.3%.

Publisher

Optica Publishing Group

Reference4 articles.

1. Highly efficient data migration and backup for big data applications in elastic optical inter-data-center networks

2. A Scalable, High-Performance, and Fault-Tolerant Network Architecture for Distributed Machine Learning

3. Predictive Analytics Based Knowledge-Defined Orchestration in a Hybrid Optical/Electrical Datacenter Network Testbed

4. Multi-FSR Silicon Photonic Flex-LIONS Module for Bandwidth-Reconfigurable All-to-All Optical Interconnects

Cited by 2 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. P4INC-AOI: When In-Network Computing Meets All-Optical Interconnect for Adaptive and Low-Latency Optical DCN;2023 Optical Fiber Communications Conference and Exhibition (OFC);2023-03

2. Application-aware Configuration of All-optical Interconnects in Hyper-FleX-LION : (Invited Paper);2022 IEEE 7th Optoelectronics Global Conference (OGC);2022-12-06

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