Jinliang Wei,韦金良
- Ph.D. student at CMU CSD since Fall, 2012.
- Advised by Garth A. Gibson and Eric P. Xing.
- Developing distributed frameworks for scaling out machine learning training applications. My work on the Bösen parameter server is part of the Petuum project, which is now a Pittsburgh-based startup.
- Generally interested in distributed systems, database systems and machine learning applications.
- B.S. in Computer Engineering, Minor in Mathematics, with Distinction from Purdue University, West Lafayette.
- CV
Research Summary
My doctoral research is focused on enabling machine learning researchers and practitioners to efficiently train large and complex models with big data on distributed clusters.
I spent a few years on developing parameter server systems to make machine learning programs run fast and efficiently and worked
on automating dependence-aware parallelization of serial, imperative ML programs for distributed training.
I am now working on dynamic scheduling (i.e., distributed device placement) for neural network training to complete my thesis.
Selected Publications
- Priority-based Parameter Propagation for Distributed DNN Training
Anand Jayarajan，Jinliang Wei, Garth A. Gibson, Alexandra Fedorova, Gennady Pekhimenko
SysML 2019, Mar 31 - April 2, 2019, Stanford, CA.
[PDF] - Automating Dependence-Aware Parallelization of Machine Learning Training on Distributed Shared Memory
Jinliang Wei, Garth A. Gibson, Phillip B. Gibbons and Eric P. Xing
EuroSys 2019, Mar 25-28, 2019, Dresden, Germany.
[PDF] - Dynamic Scheduling For Dynamic Control Flow in Deep Learning Systems
Jinliang Wei, Garth A. Gibson, Vijay Vasudevan and Eric P. Xing
Learning Systems Workshop at NeurIPS 2018, Nov, 2018, Montreal, Canada.
[PDF] - Efficient and Programmable Machine Learning on Distributed Shared Memory via Static Analysis
Jinliang Wei, Garth A. Gibson and Eric P. Xing
SysML 2018, Stanford, CA.
[PDF] - Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters
Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie and Eric P. Xing
USENIX Annual Technical Conference (ATC 2017), Jul 2017, Santa Clara, CA.
[PDF] - Addressing the Straggler Problem for Iterative Convergent Parallel ML
Aaron Harlap, Henggang Cui, Wei Dai, Jinliang Wei, Gregory R. Ganger, Phil B. Gibbons, Garth A. Gibson and Eric P. Xing.
The 7th ACM Symposium on Cloud Computing (SoCC 2016), Oct 2016, Santa Clara, CA.
[PDF] - Managed Communication and Consistency for Fast Data-Parallel Iterative Analytics
Jinliang Wei, Wei Dai, Aurick Qiao, Qirong Ho, Henggang Cui, Gregory R. Ganger, Phil B. Gibbons, Garth A. Gibson and Eric P. Xing.
The 6th ACM Symposium on Cloud Computing (SoCC 2015), Aug 2015, Kohala Coast, HI. Best Paper Award
[PDF] [slides] - Petuum: A New Platform for Distributed Machine Learning on Big Data
Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar and Yaoliang Yu. The 25th SIGKDD Conference on Knowledge Discovery and Data Mining, 2015 (KDD 2015), Aug 2015.
[arXiv PDF] - LightLDA: Big Topic Models on Modest Compute Clusters
Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu and Wei-Ying Ma.
Proc. of the International World Wide Web Conference (WWW 2015), May, 2015, Florence, Italy.
[arXiv PDF] - High-Performance Distributed ML at Scale through Parameter Server Consistency Models
Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth A. Gibson and Eric P. Xing.
Proc. of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Jan, 2015, Austin, TX.
[PDF] - Exploiting Iterative-ness for Parallel ML Computations
Henggang Cui, Alexey Tumanov, Jinliang Wei, Lianghong Xu, Wei Dai, Jesse Haber-Kucharsky, Qirong Ho, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, and Eric P. Xing
The 5th ACM Symposium on Cloud Computing (SoCC 2014), Nov 2014.
[PDF] - Exploiting Bounded Staleness to Speed Up Big Data Analytics
Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Abhimanu Kumar, Jinliang Wei, Wei Dai, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, and Eric P. Xing.
USENIX Annual Technical Conference (ATC 2014), Jun 2014.
[PDF]
Teaching Experience (CMU)
- 15-719 Advanced Cloud Computing (Spring 2017)
Instructors: Garth Gibson, Greg Ganger, Majd Sakr
Introduction to Spark programming and performance diagnosis (recitation slides) - 15-415 Database Applications (Fall 2015)
Instructors: Christos Faloutsos, Andy Pavlo
Work Experience
- Summer 2017 -- Microsoft Research, Redmond
- Summer 2015 -- HP Labs