Jinliang Wei

发表

Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters

Pengtao Xie, Eric P. Xing, Zhiting Hu, 2017, USENIX Annual Technical Conference.

Exploiting Bounded Staleness to Speed Up Big Data Analytics

Seunghak Lee, Eric P. Xing, Henggang Cui, 2014, USENIX Annual Technical Conference.

Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines pdf

Pengtao Xie, Eric P. Xing, Zhiting Hu, 2015, ArXiv.

Consistency for Fast Data-Parallel Iterative Analytics

Phillip B. Gibbons, Garth A. Gibson, E. Xing, 2015 .

Addressing the straggler problem for iterative convergent parallel ML

Eric P. Xing, Henggang Cui, Gregory R. Ganger, 2016, SoCC.

Petuum: A New Platform for Distributed Machine Learning on Big Data

Yaoliang Yu, Pengtao Xie, Seunghak Lee, 2013, IEEE Transactions on Big Data.

Managed communication and consistency for fast data-parallel iterative analytics

Eric P. Xing, Henggang Cui, Gregory R. Ganger, 2015, SoCC.

LightLDA: Big Topic Models on Modest Computer Clusters

Tie-Yan Liu, Wei-Ying Ma, Eric P. Xing, 2014, WWW.

Petuum: A Framework for Iterative-Convergent Distributed ML pdf

Seunghak Lee, Eric P. Xing, Xun Zheng, 2013, ArXiv.

Consistent Bounded-Asynchronous Parameter Servers for Distributed ML pdf

Eric P. Xing, Xun Zheng, Wei Dai, 2013, ArXiv.

Petuum: A New Platform for Distributed Machine Learning on Big Data

Yaoliang Yu, Pengtao Xie, Seunghak Lee, 2015, IEEE Trans. Big Data.

Benchmarking Apache Spark with Machine Learning Applications

Jin Kyu Kim, Jinliang Wei, 2016 .

Automating Dependence-Aware Parallelization of Machine Learning Training on Distributed Shared Memory

Eric P. Xing, Phillip B. Gibbons, Garth A. Gibson, 2019, EuroSys.

Efficient and Programmable Distributed Shared Memory Systems for Machine Learning Training

Jinliang Wei, 2018 .

Efficient and Programmable Machine Learning on Distributed Shared Memory via Static Analysis

Garth A. Gibson, Jinliang Wei, 2018 .

Extracting fiber length distributions from dual-beard fibrographs with the Levenberg–Marquardt algorithm

Jinliang Wei, Jingan Wang, Bugao Xu, 2020, Textile Research Journal.

Addressing the Long-Lineage Bottleneck in Apache Spark

Garth A. Gibson, Jinliang Wei, Haoran Wang, 2018 .

Consistency Models for Distributed ML with Theoretical Guarantees

Eric P. Xing, Xun Zheng, Wei Dai, 2013 .

Overlap Communication with Dependent Computation via Decomposition in Large Deep Learning Models

Blake A. Hechtman, Andy Davis, Jinliang Wei, 2022, ASPLOS.

High-Performance Distributed ML at Scale through Parameter Server Consistency Models pdf

Eric P. Xing, Garth A. Gibson, Wei Dai, 2014, AAAI.

Priority-based Parameter Propagation for Distributed DNN Training pdf

Gennady Pekhimenko, Garth A. Gibson, Alexandra Fedorova, 2019, SysML.

Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads pdf

Miryung Kim, Ravi Netravali, Keval Vora, 2021, OSDI.

A fuzzy multi-objective decision-making method for agent-based negotiation

Jinliang Wei, Zhou zhi, Deng Qiangang, 2003, International Conference on Natural Language Processing and Knowledge Engineering, 2003. Proceedings. 2003.

Istc-cc Update Istc-cc Research Overview Pillar 1: Specialization

Henggang Cui, Jinliang Wei, Gennady Pekhimenko, 2022 .

Customer segmentation by web content mining

Bugao Xu, Jinliang Wei, Jinfeng Zhou, 2021, Journal of Retailing and Consumer Services.

Training Larger Models on TensorFlow without Additional GPU

Garth A. Gibson, E. Xing, Jinliang Wei, 2019 .

Exploiting iterative-ness for parallel ML computations

Eric P. Xing, Wei Dai, Henggang Cui, 2014, SoCC.

LightLDA: Big Topic Models on Modest Compute Clusters

E. Xing, Qirong Ho, Wei Dai, 2014, ArXiv.