Several RA positions are open for 2018 Fall and 2019 Spring! I am looking for self-motivated students with solid CS and Math background who are interested in high-performance computing, parallel and distributed computing, big data analytics. Students with prior related experience are preferred. If you are interested, please feel free to email me your CV and transcripts.

Visiting scholars and students are also very welcome!

Short Bio

Dr. Dingwen (Devin) Tao is a faculty member in the Department of Computer Science at The University of Alabama. He received his Ph.D. degree in Computer Science and Engineering from University of California, Riverside in 2018 advised by Dr. Zizhong (Jeffrey) Chen and Dr. Franck Cappello (Argonne National Laboratory) focusing on High-Performance Computing. He obtained his B.S. degree in 2013 from College of Mathematics, University of Science and Technology of China, majoring in Information and Computing Science. Prior to joining UA, he worked as a R&D intern in the Computational Science Initiative Division at Brookhaven National Laboratory, Mathematics and Computer Science Division at Argonne National Laboratory, and High-Performance Computing Group at Pacific Northwest National Laboratory.

Dr. Dingwen Tao's current research interests include High-Performance Computing (HPC), Parallel and Distributed Computing, Big Data Analytics, Scientific Data Analysis and Reduction, Extreme-Scale Fault Tolerance and Resilience, and Large-scale Machine Learning. He has published in the major HPC and Big Data related conferences and journals, including IEEE BigData/CLUSTER/IPDPS, ACM HPDC/PPoPP, ACM/IEEE SC, IEEE TPDS, IJHPCA, etc. His research has been supported by the National Science Foundation (NSF), Department of Energy (DOE), Argonne National Laboratory, Brookhaven National Laboratory.

News

  • 08/2018: Two accpeted papers have been selected as Best Paper for each track in IEEE Cluster.
  • 07/2018: One paper has been accepted for publication in IEEE TPDS (Transaction on Parallel and Distributed Systems).
  • 07/2018: Three papers (two full and one short) got accepted by IEEE Cluster'18.
  • 06/2018: I will serve on the technical committee member for IEEE HiPC'18 and IEEE eScience'18.
  • 06/2018: One paper have been accepted for publication in IEEE/ACM SC'18. The acceptance rate is 19.1% (55/288).
  • 03/2018: One paper have been accepted for publication in ACM HPDC'18. The acceptance rate is 19.6% (22/112).
  • 10/2017: One paper have been accepted for publication in IEEE Big Data 2017.
  • 09/2017: One paper have been accepted for publication in IJHPCA (The International Journal of High Performance Computing Applications).
  • 05/2017: I was selected to receive a Dissertation Year Program (DYP) Fellowship from University of California, Riverside.
  • 01/2017: One paper have been accepted for publication in IEEE IPDPS'17.

Research Interests

  • High-Performance Computing
    • Accelerator-based computing (GPU, MIC, FPGA)
    • Extreme-scale Fault Tolerance and Resilience Techniques
    • Energy-Efficient Algorithm and Software Design
    • HPC Scientific Simulations
  • Distributed System
    • Cloud and Edge Computing
  • Big Data Analytics
    • Scientific Data Analysis and Reduction
    • Lossy Compression for Scientific Data
    • Large-scale Machine Learning
  • High-Performance Scientific Computing
    • Dense and Sparse Linear System
    • Numerical Iterative Methods

Selected Publications

TPDS'18: Sheng Di, Dingwen Tao, Xin Liang, and Franck Cappello. Efficient Lossy Compression for Scientific Data based on Pointwise Relative Error Bound. IEEE Transactions on Parallel and Distributed Systems.

Cluster'18: Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, and Franck Cappello. Fixed-PSNR Lossy Compression for Scientific Data. Proceedings of the 2018 IEEE International Conference on Cluster Computing, Belfast, UK, September 10 - 13, 2018. [ Paper ] [ Slides ]

Cluster'18: Xin Liang, Sheng Di, Dingwen Tao, Zizhong Chen, and Franck Cappello. An Efficient Transformation Scheme for Lossy Data Compression with Point-wise Relative Error Bound. Proceedings of the 2018 IEEE International Conference on Cluster Computing, Belfast, UK, September 10 - 13, 2018. [ Paper ] [ Slides ] (Best Paper Award in Data, Storage, Visualization Area)

Cluster'18: Ali Murat Gok, Sheng Di, Yuri Alexeev, Dingwen Tao, Vladimir Mironov, Xin Liang, and Franck Cappello. PaSTRI: Error-Bounded Lossy Compression for Two-Electron Integrals in Quantum. Proceedings of the 2018 IEEE International Conference on Cluster Computing, Belfast, UK, September 10 - 13, 2018. [ Paper ] [ Slides ] (Overall Best Paper Award)

SC'18: Jieyang Chen, Hongbo Li, Sihuan Li, Xin Liang, Panruo Wu, Dingwen Tao, Kaiming Ouyang, Yuanlai Liu, Qiang Guan, and Zizhong Chen. FT-MAGMA: Fault Tolerance Dense Matrix Decomposition on Heterogeneous Systems with GPUs. Proceedings of the 30th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Dallas, Texas, USA, Nov 11 - 16, 2018. Acceptance Rate: 19.1% (55/288) [ Paper ]

HPDC'18: Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, and Franck Cappello. Improving Performance of Iterative Methods by Lossy Checkponting. Proceedings of the 27th ACM International Symposium on High-Performance Parallel and Distributed Computing, Tempe, AZ, USA, June 11 - 15, 2018. Acceptance Rate: 19.6% (22/112) [ Paper ][ Slides ][ Lightning Talk ]

BigData'17: Dingwen Tao, Sheng Di, Zizhong Chen, and Franck Cappello. In-Depth Exploration of Single-Snapshot Lossy Compression Techniques for N-Body Simulations. Proceedings of the 2017 IEEE International Conference on Big Data, Boston, MA, USA, December 11 - 14, 2017. Acceptance Rate: 19.9% (87/437) [ Paper ] [ Slides ]

IJHPCA'17: Dingwen Tao, Sheng Di, Hanqi Guo, Zizhong Chen, and Franck Cappello. Z-checker: A Framework for Assessing Lossy Compression of Scientific Data. The International Journal of High Performance Computing Applications. [ Paper ] [ Software ]

SC'17: Xin Liang, Jieyang Chen, Dingwen Tao, Sihuan Li, Panruo Wu, Hongbo Li, Kaiming Ouyang, Yuanlai Liu, Fengguang Song, and Zizhong Chen. Correcting Soft Errors Online in Fast Fourier Transform. Proceedings of the 29th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, Colorado, USA, Nov 12 - 17, 2017. Acceptance Rate: 18.6% (61/327). [ Paper ]

IPDPS'17: Dingwen Tao, Sheng Di, Zizhong Chen, and Franck Cappello. Significantly Improving Lossy Compression for Scientific Data Sets Based on Multidimensional Prediction and Error-Controlled Quantization. Proceedings of the 31th IEEE International Parallel & Distributed Processing Symposium, Orlando, Florida, USA, May 29 - June 2, 2017. Acceptance Rate: 22.8% (116/508). [ Paper ] [ Slides ] [ Software ]

PPoPP'17: Panruo Wu, Nathan, Debardeleben, Qiang Guan, Sean Blanchard, Jieyang Chen, Dingwen Tao, Xin Liang, Ouyang Kaiming, Sihuan Li, and Zizhong Chen. Silent Data Corruption Resilient Two-sided Matrix Factorizations. Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Austin, Texas, USA, February 4 - 8 2017 . Acceptance Rate: 21.9%. (29/132) [ Paper ]

SC'16: Jieyang Chen, Li Tan, Panruo Wu, Dingwen Tao, Hongbo Li, Xin Liang, Sihuan Li, Rong Ge, Laxmi Bhuyan, and Zizhong Chen. GreenLA: Green Linear Algebra Software for GPU-Accelerated Heterogeneous Computing. Proceedings of the 28th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Salt Lake City, Utah, USA, Nov 13 - 18, 20 16. Acceptance Rate: 18.4% (82/446). [ Paper ]

HPDC'16: Dingwen Tao, Shuaiwen Leon Song, Sriram Krishnamoorthy, Panruo Wu, Xin Liang, Zheng Eddy Zhang, Darren Kerbyson, and Zizhong Chen. New-Sum: A Novel Online ABFT Scheme For General Iterative Methods. Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing, Kyoto, JAPAN, May 31- June 4, 2016 . Acceptance Rate: 15.5% (20/129). [ Paper ] [ Slides ]

HPDC'16: Panruo Wu, Qiang Guan, Nathan DeBardeleben, Sean Blanchard, Dingwen Tao, Xin Liang, Jieyang Chen, and Zizhong Chen. Towards Practical Algorithm Based Fault Tolerance in Dense Linear Algebra. Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing, Kyoto, JAPAN, May 31 - June 4, 2016. Acceptance Rate: 15.5% (20/129). [ Paper ]