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DINGWEN TAO

Assistant Professor in Computer Science

School of Electrical Engineering & Computer Science

Washington State University

Office: EME 406

Email: dingwen.tao@wsu.edu

Phone: +1 (509) 335-2126

 
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BIOGRAPHY

Dr. Dingwen Tao is an Assistant Professor in the School of Electrical Engineering & Computer Science at Washington State University. He also holds an Adjunct Professor position with the Department of Computer Science at the University of Alabama. He is the member of WSU High Performance Computing and Scalable Data Science Group.

Dr. Dingwen Tao received his Ph.D. in Computer Science from University of California, Riverside in 2018 and his B.S. in Mathematics from University of Science and Technology of China in 2013. Prior to joining WSU, he worked in Department of Computer Science at the University of Alabama (tenure-track assistant professor), 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 was the receipt of the 2021 R&D100 Awards Winner, 2020 IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High Performance Computing, 2020 NSF CISE Research Initiation Initiative (CRII) Award, and 2017 UCR Dissertation Year Program (DYP) Award.

Dr. Dingwen Tao's research interests include high-performance computing (HPC), parallel and distributed system, big data analytics, scientific data management, fault tolerance and resilience, and large-scale machine learning. He has published in the top-tier HPC and big data conferences and journals, including SC, ICSHPDC, PPoPP, DACPACT, IPDPSCLUSTER, ICPP, BigData, IEEE TCIEEE TPDS, etc. He has been working closely with multiple teams teams and scientists from the Argonne National Lab, Los Alamos National Lab, Brookhaven National Laboratory, Oak Ridge National Lab, and Pacific Northwest National Lab. His research has been supported by NSF, DOE, NOAA, AMD and Xilinx. For more details, please refer to his CV (EnglishChinese, short version).

WSU ranks #47 in Washington Monthly's 2020 list of top public universities. WSU EECS ranks #7 in design automation, #17 in HPC, #54 in database, #57 in AI, #61 in all system areas, and #74 in all areas, according to CSRankings. WSU CS graduate program ranks #75 in U.S. according to US News Rankings.

I am always looking for outstanding Ph.D. and undergraduate students who are interested in the area of HPC, computing systems, data analytics, and machine learning. Details can be found here. Please send me your CV and transcript to me.

 

LATEST NEWS

  • 11/2021: I joined the Editorial Board of IEEE Transactions on Parallel & Distributed Systems (TPDS).

  • 11/2021: Our cuSZ+ work has been selected as the 3rd Place Winner of the ACM Student Research Competition at SC'21! Congratulations to Jiannan! 

  • 11/2021: One paper has been accepted for publication in VLDB'22. Congratulations to Sian!

  • 11/2021: Our project and award has been featured by WSU Insider!

  • 10/2021: Our SZ compression software has been selected for 2021 R&D100 Awards! [ News ]

  • 08/2021: Our SZ compression framework has been selected as one of the Finalists of 2021 R&D100 Awards!!

  • 08/2021: A 280k CSSI project was funded by NSF (my role: single PI). Thanks a lot to NSF! 

  • 07/2021: A 25k project for "FAIR Surrogate Benchmarks Supporting AI and Simulation Research" is sub-awarded by Argonne National Lab (my role: single PI). Thanks a lot to ANL! 

  • 07/2021: Four papers have been accepted for publication in IEEE Cluster'21! Congratulations to Daoce and Jiannan! 

  • 05/2021: One paper has been accepted for publication in IEEE Transactions on Computers. Congratulations to Xin!

  • 05/2021: Thanks to Xilinx for donating Alveo data center acclerator card to my group!

  • 05/2021: My NSF CRII project's REU supplement has been awarded. Thanks a lot to NSF! Please contact me If you are interested in undergraduate research opportunities (with stipend). [REU Project Website]

  • 04/2021: We have been grated to access NSF-funded Ookami HPC at Stony Brook (equipped with A64FX CPU). Thanks for NSF and SBU's support!

  • 04/2021: Boyuan Zhang and Xinyu Chen accepted our PhD offers. Looking  forward to their join!

  • 04/2021: Daoce got an internship offer from LANL Data Science at Scale School. Congratulations to Daoce!

  • 03/2021: One paper has been accepted for publication in ICS'21! Congratulations to Chengming!

  • 03/2021: One paper has been accepted for publication in HPDC'21! Congratulations to Sian!

  • 02/2021: One paper has been accepted for publication in JPDCCongratulations to Cody!

  • 02/2021: Cody got an intern offer from DOE Science Undergraduate (SULI) program! Congratulations to Cody!

  • 01/2021: Chengming got an internship offer from Facebook Reality Labs to work on on-device machine learning! Congratulations to Chengming!

  • 01/2021: Baixi Sun joined HiPDAC as a PhD student. Welcome Baixi!

  • 12/2020: One paper has been accpeted for publication in IPDPS'21! Congratulations to Jiannan!

  • 12/2020: I'll serve as a panelist for NSF CSSI Program. Thanks for NSF's invitation!

  • 12/2020: I'll serve as an external reviewer for NASA EPSCoR CAN Program. Thanks for NASA's invitation!

  • 12/2020: A 20K gift is awarded by AMD through FlapMX. Thanks a lot to both AMD and FlapMX!

  • 12/2020: A 64K project for "Exploring Multiresolution Based Compression for Extreme-Scale Scientific Applications" is awarded by Argonne National Lab (my role: single PI). Thanks a lot to ANL!

  • 11/2020: Two papers have been accepted by PPoPP'21 as poster. Congratulations to Sian!

  • 10/2020: A talk "Improving HPC and AI Systems and Applications Using Error-Bounded Lossy Compression " was given to School of Computer Science and Technology at USTC. [ Flyer ]

  • 10/2020: I will serve as the Lead Guest Editor of the special issue Scalable Computing Systems and Networks in Supercomputing in Journal of Supercomputing. Please consider a submission to IEEE ScalCom'21. 

  • 10/2020: Congratulations to Sian for being awarded the Mahmoud M. Dillsi Family Graduate Fellowship for the 2020‐2021 academic year! [ News ]

  • 09/2020: I was very honored to be selected for 2020 IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High Performance Computing. [ IEEE News ] [ WSU News ]

  • 09/2020: The GPU/CUDA version of SZ (called cuSZ) has been officially released in GitHub

  • 08/2020: Daoce Wang joined HiPDAC as a PhD student. Welcome Daoce!

  • 08/2020: The official website of our SZ lossy compressor framework (http://szcompressor.org/) has been established.

  • 08/2020: A $64K project for "Improving GPU version of SZ for Scientific Applications at Extreme Scale" is awarded by Argonne National Lab (my role: single PI). Thanks a lot to ANL!

  • 08/2020: Congratulations to Sian and Jiannan for being selected as SC'20 Student Volunteers!

  • 08/2020: I will serve as Program Co-Chair for the 21st IEEE International Conference on Scalable Computing & Communications​ (ScalCom 2021). Please consider a submission.

  • 08/2020: I am excited to be invited to attend NSF workshop on cyberinfrastructure workforce development (CyberTraining). Thanks for NSF's invitation!

  • 07/2020: A $530K collaborative CDS&E project (with Sheng Di from UChicago) has been funded by NSF (my role: lead PI). Many thanks to NSF!

  • 07/2020: One paper has been accepted for publication in PACT'20! Congratulations to Jiannan!

  • 07/2020: Our group got a donation of about $7,000 hardware and software from Xilinx, Inc. Thanks a lot to Xilinx!

  • 05/2020: One paper has been accepted for publication in ICPP'20!

  • 05/2020: A $400K CC* project (with Jeff Carver, Xiaoyan Hong, David Dixon from UA) was funded by NSF (my role: co-PI). Many thanks to NSF!

  • 04/2020: A $175K CRII project was funded by NSF (my role: single PI). Many thanks to NSF!

  • More [...]

 

RESEARCH INTERESTS

Include but not limited to:

  • High-performance computing

  • Scientific data compression

  • GPU and FPGA acceleration

  • Computational storage

  • Cloud computing (e.g., Cloud HPC)

  • Distributed machine/deep learning

  • Numerical algorithms and simulations

  • Trustworthy scientific computing

  • Quantum computing

Tao-WordCloud.png
 

SELECTED GRANTS

  • NSF, PI (single), CSSI: Elements: ROCCI: Integrated Cyberinfrastructure for In Situ Lossy Compression Optimization Based on Post Hoc Analysis Requirements, $280K, 2021-2024. [ Abstract ]

  • NSF, PI (single), CDS&E: HyLoC: Objective-driven Adaptive Hybrid Lossy Compression Framework for Extreme-Scale Scientific Applications, $270K, 2020-2023. [ Abstract ]

  • NSF, PI (single), CRII: OAC: An Efficient Lossy Compression Framework for Reducing Memory Footprint for Extreme-Scale Deep Learning on GPU-Based HPC Systems, $185K, 2020-2022. [ Abstract ]

  • NSF, co-PI, CC* Compute: Accelerating Advances in Science and Engineering at The University of Alabama Through HPC Infrastructure, $400K, 2020-2022. [ Abstract ]

 

AWARDS

  • R&D 100 Awards Winner, 2021

  • IEEE TCHPC Early Career Researchers Award for Excellence in HPC, 2020

  • NSF CISE Research Initiation Initiative (CRII) Award, 2020

  • IEEE Cluster Best Paper Award, 2018

  • UCR Dissertation Year Program (DYP) Award, 2017

  • UCR Dean’s Distinguished Fellowship, 2013

 

SELECTED PUBLICATIONS

(with my students underlined, *corresponding author)

top-cs: top-tier Computer Science publication venue according to CSRankings

top-cr: top-tier Computer Science publication venue according to Conference Ranks

VLDB'22

top-cs, top-cr

Sian Jin, Chengming Zhang, Jiannan Tian, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao*.

COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression. Proceedings of the 48th International Conference on Very Large Data Bases, Australia, September 5-9, 2022.  [ Paper ]

CLUSTER'21

top-cr

Jiannan Tian, Sheng Di, Xiaodong Yu, Cody Rivera, Kai Zhao, Sian Jin, Yunhe Feng, Xin Liang, Dingwen Tao*, Franck Cappello.

Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs. Proceedings of the 2021 IEEE International Conference on Cluster Computing, Portland, OR, USA, September 7-10, 2021. Acceptance Rate: 29% (48/163) [ Paper ] [ Slides

ACM Student Research Competition 3rd Place Winner

CLUSTER'21

top-cr

Bo Fang, Daoce Wang, Sian Jin, Quincey Koziol, Zhao Zhang, Qiang Guan, Suren Byna, Sriram Krishnamoorthy, Dingwen Tao* (1st/2nd authors contributed equally).

Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights. Proceedings of the 2021 IEEE International Conference on Cluster Computing, Portland, OR, USA, September 7-10, 2021. Acceptance Rate: 29% (48/163) [ Paper ] [ Slides ]

ICS'21

top-cs, top-cr

Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, and Dingwen Tao*.

ClickTrain: Efficient and Accurate End-to-End Deep Learning Training via Fine-Grained Architecture-Preserving Pruning.

Proceedings of the 35th ACM International Conference on Supercomputing, Virtual Event, USA, June 14-17, 2021. Acceptance Rate: 24% (38/157) [ Paper ] [ Slides ]

HPDC'21

top-cs, top-cr

Sian Jin, Jesus Pulido, Pascal Grosset, Jiannan Tian, Dingwen Tao*, and James Ahrens.

Adaptive Configuration of In Situ Lossy Compression for Cosmology Simulations via Fine-Grained Rate-Quality Modeling.

Proceedings of the 30th ACM International Symposium on High-Performance Parallel and Distributed Computing, Virtual Event, Sweden, June 21-25, 2020. Acceptance Rate: 21% (19/92). [ Paper ] [ Slides ]

IPDPS'21

top-cr

Jiannan Tian, Cody Rivera, Sheng Di, Jieyang Chen, Xin Liang, Dingwen Tao*, and Franck Cappello.

Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures.

Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, Portland, Oregon, May 17-21, 2021. Acceptance Rate: 22% (105/462) [ Paper ] [ Slides ] [ Talk ]

ELSEVIER JPDC

impact factor: 2.296

Cody Rivera, Jieyang Chen, Nan Xiong, Jing Zhang, Shuaiwen Leong Song, and Dingwen Tao*.

TSM2X: High-Performance Tall-and-Skinny Matrix-Matrix Multiplication on GPUs.

Journal of Parallel and Distributed Computing 151 (2021): 70-85. [ Paper ] [ Code

PPOPP'21

top-cr

Sian Jin, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao*.

A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression.

Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Virtual, February 27 - March 3, 2021. [ Paper ] [ Slides ] [ Talk ]

PPOPP'21

top-cr

Heng Zhang, Lingda Li, Donglin Zhuang, Rui Liu, Shuang Song, Dingwen Tao, Yanjun Wu, Shuaiwen Leon Song. 

Bring Orders into Uncertainty: Efficient Uncertain Graph Processing via Novel Path Sampling on Multi-GPU Systems.

Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Virtual, February 27 - March 3, 2021. [ Paper ]

PACT'20

top-cr

Jiannan Tian, Sheng Di, Kai Zhao, Cody Rivera, Megan Hickman, Robert Underwood, Sian Jin, Xin Liang, Jon Calhoun, Dingwen Tao*, and Franck Cappello.

cuSZ: An Efficient GPU Based Error-Bounded Lossy Compression Framework for Scientific Data.

Proceedings of the 29th ACM International Conference on Parallel Architectures and Compilation Techniques, Atlanta, GA, USA, October 3-7, 2020. Acceptance Rate: 25% (35/137)  [ Paper ] [ Slides ] [ Talk​ ] [ Code ]

ICPP'20

top-cr

Zhenbo Hu, Xiangyu Zou, Wen Xia, Sian Jin, Dingwen Tao, Yang Liu, Weizhe Zhang, and Zheng Zhang.

Delta-DNN: Efficiently Compressing Deep Neural Networks via Exploiting Floats Similarity.

Proceedings of the 49th International Conference on Parallel Processing, Edmonton, AB, Canada, August 17-20 2020. Acceptance Rate: 28% (78/269). [ Paper ] [ Talk ]

HPDC'20

top-cs, top-cr

Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Zizhong Chen, and Franck Cappello.

Significantly Improving Lossy Compression for HPC Datasets with Second-Order Prediction and Parameter Optimization.

Proceedings of the 29th ACM International Symposium on High-Performance Parallel and Distributed Computing, Stockholm, Sweden, June 23-26, 2020. Acceptance Rate: 22% (16/71). [ Paper ] [ Talk ]

IPDPS'20

top-cr

Sian Jin, Pascal Grosset, Christopher M. Biwer, Jesus Pulido, Jiannan Tian, Dingwen Tao*, and James Ahrens.

Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations.

Proceedings of the 34th IEEE International Parallel and Distributed Processing Symposium, New Orleans, LA, May 18-22, 2020. Acceptance Rate: 24% (110/446) [ Paper ] [ Slides ] [ Code ]

PRIOR TO WSU

DAC'20

top-cs, top-cr

Peiyan Dong, Siyue Wang, Wei Niu, Chengming Zhang, Sheng Lin, Zhengang Li, Yifan Gong, Bin Ren, Xue Lin, and Dingwen Tao*.

RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition.

Proceedings of the 57th Annual Design Automation Conference, San Francisco, CA, USA, July 19-23, 2020. Acceptance Rate: 23% (228/984). [ Paper ] [ Talk ]

IEEE TPDS

top journal, impact factor: 4.181

Xiangyu Zou, Tao Lu, Wen Xia, Xuan Wang, Weizhe Zhang, Haijun Zhang, Sheng Di, Dingwen Tao, and Franck Cappello.

Performance Optimization for Relative-Error-Bounded Lossy Compression on Scientific Data.

IEEE Transactions on Parallel and Distributed Systems 31, no. 7 (2020): 1665-1680. [ Paper ]

PPOPP'20

top-cr

Jiannan Tian, Sheng Di, Chengming Zhang, Xin Liang, Sian Jin, Dazhao Cheng, Dingwen Tao*, and Franck Cappello.

waveSZ: A Hardware-Algorithm Co-Design of Efficient Lossy Compression for Scientific Data.

Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, San Diego, California, USA, February 22-26, 2020. Acceptance Rate: 23% (28/121)  [ Paper ] [ Slides ]

HPDC'19

top-cs, top-cr

Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao*, and Franck Cappello.

DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression.

Proceedings of the 28th ACM International Symposium on High-Performance Parallel and Distributed Computing, Phoenix, AZ, USA, June 24-28, 2019. Acceptance Rate: 20% (22/106) [ Paper ] [ Slides ] [ Code ]

IEEE TPDS

top journal, impact factor: 4.181

Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, and Franck Cappello.

Optimizing Lossy Compression Rate-Distortion from Automatic Online Selection between SZ and ZFP.

IEEE Transactions on Parallel and Distributed Systems 30, no. 8 (2019): 1857-1871. [ Paper ]

SAGE IJHPCA

impact factor: 1.625

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 33, no. 2 (2019): 285-303. [ Paper ] [ GitHub ]

IEEE TPDS

top journal, impact factor: 4.181

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 30, no. 2 (2018): 331-345. [ Paper ]

SC'19

top-cs, top-cr

Xin Liang, Sheng Di, Sihuan Li, Dingwen Tao, Bogdan Nicolae, Zizhong Chen, and Franck Cappello.
Significantly Improving Lossy Compression Quality based on An Optimized Hybrid Prediction Model.

Proceedings of the 31st ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, Colorado, USA, Nov 17-22, 2019. Acceptance Rate: 22% (78/344) [ Paper ]

ICS'19

top-cs, top-cr

Jieyang Chen, Nan Xiong, Xin Liang, Dingwen Tao, Sihuan Li, Kaiming Ouyang, Kai Zhao, Nathan DeBardeleben, Qiang Guan, and Zizhong Chen.

TSM2: Optimizing Tall-and-Skinny Matrix-Matrix Multiplication on GPUs.

Proceedings of the 33rd ACM International Conference on Supercomputing, Phoenix, AZ, USA, June 26-28, 2019. Acceptance Rate: 23% (45/193) [ Paper ] [ Slides ] [ Code ]

BIGDATA'19

Donglin Yang, Wei Rang, Dazhao Cheng, Yu Wang, Jiannan Tian, and Dingwen Tao

Elastic Executor Provisioning for Iterative Workloads on Apache Spark.

Proceedings of 2019 IEEE International Conference on Big Data, Los Angeles, CA, USA, December 9-12, 2019. Acceptance Rate: 19% (106/550). [ Paper ]

BIGDATA'19

Yuqi Fu, Shaolun Zhang, Jose Terrero, Ying Mao, Guangya Liu, Sheng Li, and Dingwen Tao

Progress-based Container Scheduling for Short-lived Applications in a Kubernetes Cluster.

Proceedings of 2019 IEEE International Conference on Big Data, Los Angeles, CA, USA, December 9-12, 2019. Acceptance Rate: 19% (106/550). [ Paper ]

CLUSTER'19

top-cr

Xin Liang, Sheng Di, Dingwen Tao, Sihuan Li, Bogdan Nicolae, Zizhong Chen, and Franck Cappello.

Improving Performance of Data Dumping with Lossy Compression for Scientific Simulation.

Proceedings of the 2019 IEEE International Conference on Cluster Computing, Albuquerque, New Mexico USA, September 23-26, 2019. Acceptance Rate: 27% (39/141) [ Paper ]

BIGDATA'18

Xin Liang, Sheng Di, Dingwen Tao, Sihuan Li, Shaomeng Li, Hanqi Guo, Zizhong Chen, and Franck Cappello.

Error-Controlled Lossy Compression Optimized for High Compression Ratios of Scientific Datasets.

Proceedings of the 2018 IEEE International Conference on Big Data, Seattle, WA, USA, December 10-13, 2018. Acceptance Rate: 18% (98/518) [ Paper ] [ Slides ]

CLUSTER'18

top-cr

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 Chemistry.

Proceedings of the 2018 IEEE International Conference on Cluster Computing, Belfast, UK, September 10-13, 2018. Acceptance Rate: 0.6% (1/164) [ Paper ] [ Slides ] [ Code

Best Paper Award

CLUSTER'18

top-cr

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. Acceptance Rate: 2% (4/154) [ Paper ] [ Slides ] [ Code ]

Best Paper Award in Data, Storage, Visualization Area

CLUSTER'18

top-cr

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. Acceptance Rate: 31% (49/154) [ Paper ] [ Slides ]

PRIOR TO UA


HPDC'18

top-cs, top-cr

Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, and Franck Cappello.

Improving Performance of Iterative Methods by Lossy Checkpointing.

Proceedings of the 27th ACM International Symposium on High-Performance Parallel and Distributed Computing, Tempe, AZ, USA, June 11-15, 2018. Acceptance Rate: 19% (22/112) [ Paper ][ Slides ] [ Code

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% (87/437) [ Paper ] [ Slides ]

IPDPS'17

top-cr

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 31st IEEE International Parallel and Distributed Processing Symposium, Orlando, Florida, USA, May 29-June 2, 2017. Acceptance Rate: 22% (116/508). [ Paper ] [ Slides ] [ Code ]

HPDC'16

top-cs, top-cr

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% (20/129). [ Paper ] [ Slides ]

 

SOFTWARE

If you are not familiar with compression, there is a show called Silcon Valley (TV series), which will give you an idea how compression evolves our lives. Highly recommended!​

 

SERVICES

ORGANIZATION COMMITTEE

  • Program Co-chair of 2021 IEEE International Conference on Scalable Computing & Communications (ScalCom)

  • Program Co-chair of the 1st and 2nd International Workshop on Big Data Reduction (IWBDR) co-held with IEEE BigData 2020 and 2021

  • Program Co-chair of the 1st and 2nd International Workshop on Big Data Analytics of Cyber-Physical Systems (CPSBigData) co-held with IEEE IGSC 2019 and 2020

GRANT REVIEW

  • Panelist for U.S. National Science Foundation in 2021

  • Proposal Reviewer for U.S. National Aeronautics and Space Administration in 2020

TECHNICAL PROGRAM COMMITTEE

  • IEEE/ACM SC 2022

  • IEEE ICMLA 2021, IEEE HiPC 2021, IEEE IPDPS 2021, IEEE Cluster 2021, IEEE BigData 2021

  • IEEE/ACM SC 2020, IEEE Cluster 2020, IEEE Big Data 2020, ICPP 2020, IFIP NPC 2020, IEEE SCC 2020

  • IEEE HiPC 2019, IFIP NPC 2019, IEEE BigData Congress 2019, IEEE SCC 2019

  • IEEE HiPC 2018, IFIP NPC 2018, IEEE BigData Congress 2018, IEEE eScience 2018

JOURNAL REVIEWER

IEEE Transactions on Computers / Parallel and Distributed Systems / Cloud Computing / Big Data / Sustainable Computing / Smart Grid / Emerging Topics in Computing, IEEE Access, SIAM Journal on Scientific Computing, Scientific Programming, Parallel Computing, Journal of Supercomputing, Journal of Systems Architecture, Integration the VLSI Journal

 

TEACHING

UNDERGRADUATE COURSE

  • WSU CS 233 - Advanced Data Structures [Spring 2021, Fall 2021]: This course introduces data structures, beyond what was already covered in the introductory data structures class CS 132, as well as algorithm design using different data structures and algorithmic techniques.

  • WSU CS/EE 455 - Introduction to Computer Networks [Fall 2020, Fall 2021]: This course introduces concepts and implementations of computer networks, architectures, protocol layers, internetworking and addressing case studies.

  • UA CS 470 - Computer Algorithms [Fall 2019]: This course introduces construction of efficient algorithms, i.e., divide-and-conquer, dynamic programming, greedy method, max flow and matchings, parallel algorithms, string matching, computational geometry, NP-completeness.

  • UA CS 491 - High Performance Computing [Spring 2019]: This course introduces knowledge and fundamental concepts of high performance computing as well as hands-on experience of the core technology in the field. The objective of this class is to understand how to achieve high performance on a wide range of computational platforms. 

GRADUATE COURSE

  • WSU CS 580 - Advanced Topics in Computer Science [Spring 2022]: This course introduces data reduction techniques and tools for scientific applications, including a series of introductory lectures on classic compression algorithms, dimensionality reduction methods, and emerging scientific data compressors, as well as design and use of data quality assessment methods and tools in real-world applications.

  • UA CS 570 - Computer Algorithms [Fall 2019]: This course introduces construction of efficient algorithms, i.e., divide-and-conquer, dynamic programming, greedy method, max flow and matchings, parallel algorithms, string matching, computational geometry, NP-completeness.

  • UA CS 591 - High Performance Computing [Spring 2019]: This course introduces knowledge and fundamental concepts of high performance computing as well as hands-on experience of the core technology in the field.

 

WELCOME TO VISIT!