Communication-centric cross-stack acceleration for distributed machine learning

Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Li, Youjie

Contributors dc:contributor

• Kim, Nam Sung
• Hwu, Wen-mei
• Torrellas, Josep
• Chen, Deming

• Distributed Machine Learning
• Distributed Training
• Parallel Computing
• In-network Computing
• Smart Nics
• Programmable Switches
• Pipelined Sgd
• Machine Learning Framework

Statement dc:rights

• In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of [university/educational entity's name goes here]'s products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink.

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/117774

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/117774