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商品コード: 9781680837056

Coded Computing: Mitigating Fundamental Bottleneck

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書名

Coded Computing: Mitigating Fundamental Bottlenecks in Large-scale Distributed Computing and Machine Learning
シリーズ名 Foundations and Trends in Communications and Information Theory (Vol. 17, Issue 1)
著者・編者 Li, S. & Avestimehr, S.
出版社/発行元 Now publishers
発行年/月 2020年7月   
装丁 電子ブック
ページ数/巻数 160 ページ
ISBN 978-1-68083-705-6

 


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Description

 

Recent years have witnessed a rapid growth of large-scale machine learning and big data analytics, facilitating the developments of data intensive applications like voice/image recognition, real-time mapping services, autonomous driving, social networks, and augmented/virtual reality. These applications are supported by cloud infrastructures composed of large datacenters.

The large scale distributed machine learning/data analytics systems provide the necessary processing power to handle these applications, but suffer three major performance bottlenecks; namely, communication, straggler and security.

In this ground-breaking monograph, the authors introduce the novel concept of Coded Computing. Coded Computing exploits coding theory to optimally inject and leverage data/task redundancy in distributed computing systems, creating coding opportunities to overcome the bottlenecks.

After introducing the reader to the core of the problem, the authors describe in detail each of the bottlenecks that can be overcome using Coded Computing. The monograph provides an accessible introduction into how this new technique can be used in developing large-scale computing systems.

 

Contents:

 

1. Introduction
2. Coding for Bandwidth Reduction
3. Coding for Straggler Mitigation
4. Coding for Security and Privacy
Acknowledgements
Appendices
References

 

 

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