Da Li's Homepage

News

Passed Doctoral Defense
Paper Accepted by SustainCom'16

Research interests

Parallel Computing: optimization, programming model, compiler and runtime for many-core
Machine Learning: building large-scale machine learning systems, GPU accelerated machine learning
Embedded System: GPU computing on embedded systems, mobile computing

Work Experience:

Facebook (2016 - present)
Sony U.S. Research Center (2015)
AT&T Labs Research America (2014)
NEC Laboratories America (2013)
Taobao, Alibaba Group (2011)

Publications

Facilitating Emerging Applications on Many-core Processors
Da Li [ PDF ]
Dissertation , Columbia, MO, USA, July, 2016.

Evaluating the Energy Efficiency of Deep Convolutional Neural Networks on CPUs and GPUs
Da Li*, Xinbo Chen*, Michela Becchi, Ziliang Zong (* both are leading authors) [ PDF ]
In IEEE International Conference on Sustainable Computing and Communications (SustainCom '16) , Atlanta, GA, USA, October, 2016.

Compiler-Assisted Workload Consolidation for Efficient Dynamic Parallelism on GPU
Hancheng Wu*, Da Li*, Michela Becchi (* both are leading authors) [ PDF ]
In IEEE International Parallel & Distributed Processing Symposium (IPDPS '16) , Chicago, Illinois, USA, May, 2016.

Facilitating Irregular Applications on Many-Core Processors
Da Li [ Paper , Slides , Poster ]
In International Conference for High Performance Computing, Networking, Storage and Analysis (SC '15 Doctoral Showcase) , Austin, TX, USA, November 2015.

Nested Parallelism on GPU: Exploring Parallelization Templates for Irregular Loops and Recursive Computations
Da Li, Hancheng Wu, Michela Becchi [ PDF ]
In International Conference on Parallel Processing (ICPP '15) , Beijing, China, September, 2015.

Exploiting Dynamic Parallelism to Efficiently Support Irregular Nested Loops on GPUs
Da Li, Hancheng Wu, Michela Becchi [ PDF ]
In International Workshop on Code OptimiSation for Multi and Many Cores (COSMIC '15) , San Francisco Bay Area, CA, Feburary, 2015.

GRapid: a Compilation and Runtime Framework for Rapid Prototyping of Graph Applications on Many-core Processors
Da Li, Srimat Chakradhar, Michela Becchi [ PDF ]
In IEEE International Conference on Parallel and Distributed Systems (ICPADS '14) , Hsinchu, Taiwan, December, 2014.

Large-Scale Pairwise Alignments on GPU Clusters: Exploring the Implementation Space
Huan Truong, Da Li, Kittisak Sajjapongse, Gavin Conant, Michela Becchi [ PDF ]
In Journal of Signal Processing Systems , Volume 77, Issue 1-2, October, 2014.

A Distributed CPU-GPU Framework for Pairwise Alignments on Large-Scale Sequence Datasets
Da Li, Kittisak Sajjapongse, Huan Truong, Gavin Conant, Michela Becchi [ PDF ]
In IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP '13) , Washington D.C., USA, June, 2013.

Deploying Graph Algorithms on GPUs: an Adaptive Solution
Da Li, Michela Becchi [ PDF ]
In IEEE International Parallel & Distributed Processing Symposium (IPDPS '13) , Boston, Massachusetts, USA, May, 2013.

Multi-Source Data Oriented Flexible Real-time Information Fusion Platform on FPGA
Tian Song, Da Li, Ying Yao [ PDF ]
In IEEE International Conference on Electronics, Communications and Control (ICECC '11) , Ningbo, China, September, 2011.

Posters

Designing Code Variants for Applications with Nested Parallelism on GPUs
Da Li, Michela Becchi [ Poster ]
In GPU Technology Conference (GTC '15) , Silicon Valley, CA, USA, March 2015.

Multiple Pairwise Sequence Alignments with the Needleman-Wunsch Algorithm on GPU
Da Li, Michela Becchi [ Paper , Poster ]
In International Conference for High Performance Computing, Networking, Storage and Analysis (SC '12) , Salt Lake City, UT, USA, November 2012.

Software Support for Regular and Irregular Applications in Parallel Computing
Da Li, Michela Becchi [ Slides , Poster ]
In International Conference for High Performance Computing, Networking, Storage and Analysis (SC '12) , Salt Lake City, UT, USA, November 2012.

Patents

Learning Convolution Neural Networks on Heterogeneous CPU-GPU Platform (July 2015, Application No.15/217,475)
Ming-Chang Liu, Xun Xu, Da Li

Source-to-source Transformations for Graph Processing on Many-core Platforms (May 2016, Patent No.9335981)
Srimat Chakradhar, Michela Becchi, Da Li

A Multiple String Matching Method for Search Engine (December 2012, Patent No.201010232463.2)
Tian Song, Da Li