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Zhifeng Lin

Software Engineer at Google

About Me

  • A true trojan with my BSEE, MSEE, and MSCS all from USC :)
  • Fruitful research experience in distributed system designs for machine learning
  • Strong software & firmware development skills learned and continuously learning from the industry

Experience

Google

Software Engineer

Google Cloud team

USC Viterbi School of Engineering

Research & Teaching Assistant

  • Conducted research in distributed systems for machine learning
  • TA in Fall 2018 for EE250, Distrubuted Systems & the Internet of Things
  • TA in Spring 2017 for EE457, Computer System Organizations
  • TA in Fall 2016 for EE352, Computer Organization and Architecture

AMD Research

Research Co-Op Engineer

Conducted research for On-Chip-Network of SoC in area of routing algorithms and Quality of Service as part of the DOE FastForward2 project

AMD Research

Research Co-Op Engineer

Designed and implemented an assembly methodology framework to drive simulations in the exascale computing research domain to serve the DOE FastForward project

Spirent Communications

Firmware Engineer

  • Worked with other engineers from HW/SW teams and also Marketing in an Agile-Scrum setting to develop/maintain programs in Infrastructure Layer and Business Logic Layer of the software stack
  • Designed and developd "virtual hardware" components such as "virtual FPGAs" and "virtual PHY chips" to improve testing capability and increase code coverage for the actual products

Education

University of Southern California

August 2017 - May 2019

Master of Science in Computer Science

University of Southern California

August 2014 - December 2015

Master of Science in Electrical Engineering

University of Southern California

August 2011 - December 2013

Bachelor of Science in Electrical Engineering

Publications

GradiVeQ

Mingchao Yu*, Zhifeng Lin*(Equal Contributions), Krishna Narra, Songze Li, Youjie Li, Nam Sung Kim, Alexander Schwing, Murali Annavaram, Salman Avestimehr. GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN training. In the 31st Annual Conference on Neural Information Processing Systems (NeurIPS), Montreal, Quebec, Canada, December 2018

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S2C2

Krishna Giri Narra*, Zhifeng Lin*(Equal Contributions), Mehrdad Kiamar, Salman Avestimehr, Murali Annavaram. Slack Squeeze Coded Computing for Adaptive StragglerMitigation. To appear in the International Conference for High Performance Computing Networking, Storage, and Analysis 2019 (SC19), Denver, CO, November 2019

Modular Routing Design for Chiplet-based Systems

Jieming Yin, Zhifeng Lin, Onur Kayiran, Matthew Poremba, Muhammad Shoaib Bin Altaf, Natalie Enright Jerger, Gabriel H. Loh. Modular Routing Design for Chiplet-based Systems. In the Proceedings of the 45th International Symposium on Computer Architecture (ISCA), Los Angeles, CA, June 2018

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Collage Inference

Krishna Giri Narra, Zhifeng Lin, Ganesh Ananthanarayanan, Salman Avestimehr, Murali Annavaram. Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models. CodML workshop (Workshop on Coding Theory For Large-scale Machine Learning) at the 36th International Conference on Machine Learning (ICML), Long Beach, CA, June 2019

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Unified and Flexible Methodology for System Specification and Evaluation

Zhifeng Lin, Yasuko Eckert, Gabriel H. Loh. Unified and Flexible Methodology for System Specification and Evaluation. Workshop on Modeling & Simulation of Systems and Application 2016 (ModSim), University of Washington, Seattle, WA, August 2016

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Skills