DINGWEN TAO
Associate Professor of Intelligent Systems Engineering
Associate Professor of Data Science
Luddy School of Informatics, Computing, & Engineering
Indiana University Bloomington
Office: Luddy Hall 4124
Email: ditao@iu.edu
Phone: +1 (812) 855-2822
BIOGRAPHY
Dr. Dingwen Tao is a Tenured Associate Professor in the Luddy School of Informatics, Computing, and Engineering at Indiana University Bloomington. He 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.
Dr. Dingwen Tao worked as an Assistant Professor at Washington State University and University of Alabama between 2018~2022. Prior to that, he worked in the Computational Science Initiative at Brookhaven National Laboratory, the Mathematics and Computer Science Division at Argonne National Laboratory, and the High-Performance Computing Group at Pacific Northwest National Laboratory. He is serving as an Associate Editor of IEEE Transactions on Parallel and Distributed Systems (TPDS).
Dr. Dingwen Tao is the recipient of the NSF CAREER Award (2023), Amazon Research Award (2022), Meta Research Award (2022), R&D100 Awards Winner (2021), IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High Performance Computing (2020), NSF CISE Research Initiation Initiative (CRII) Award (2020), IEEE CLUSTER Best Paper Award (2018), UCR Dissertation Year Program (DYP) Award (2017). According to CSRankings in HPC (2018-2023), he ranks #1 in U.S. and #2 in the world. He is a Senior Member of ACM and IEEE.
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, ICS, HPDC, PPoPP, DAC, PACT, IPDPS, CLUSTER, ICPP, BigData, IEEE TC, IEEE TPDS, etc. He has been working closely with multiple 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, Meta, AMD, and Xilinx. For more details, please refer to his CV (English, Chinese) and Statements (Research, Teaching, and Service).
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 and 1point3acres. Please send me your CV and transcript to me.
LATEST NEWS
4/2024: I received an official letter from the President about my successful tenure at IU. Many thanks to my students, colleagues, and collaborators!
4/2024: Chengming Zhang has received an assistant professor offer from University of Houston. Big congratulations to Chengming!
2/2024: One paper has been accepted for publication in DAC'24.
2/2024: I start to serve a Subject Associate Editor (SAE) for the Parallel Computing (ParCo) journal.
1/2024: One paper has been accepted for publication in VLDB'24.
1/2024: One paper has been accepted for publication in DCC'24.
12/2023: One paper has been accepted in IEEE TPDS.
11/2023: I am glad to give a talk at Rutgers REFAI Seminar about our ML Systems Research! [ Video ]
10/2023: I was elevated to ACM Senior Member.
10/2023: I start to serve as an Associate Editor for the IEEE Transaction on Parallel and Distributed Systems (TPDS). Please consider to submit your pioneering work to TPDS!
09/2023: One paper has been accepted for publication in EuroSys'24.
08/2023: Congratulations to Chengming on receiving a research scientist offer from Microsoft Research!
08/2023: A $600K project in collaboration with U. Rochester was funded by NSF (my role: Site PI). Many thanks to the NSF!
08/2023: I'll give three talks at HPC China 2023, UH ECE Seminar, and AMD Tech Talks in the coming weeks!
07/2023: A $3.2M CSSI project in collaboration with UChicago, OSU, and UAB was funded by NSF (my role: Site PI). Many thanks to the NSF!
06/2023: I was elevated to IEEE Senior Member.
06/2023: Two papers have been accepted for publication in SC'23.
06/2023: I'm serving as the lead guest editor for the Special Issue on "Advances in Lossy Data Compression Techniques" in the Electronics Journal. Please consider making a submission!
05/2023: I'm serving as the program committee chair of the 9th International Workshop on Data Reduction for Big Scientific Data (DRBSD-9) at SC'23. Please consider making a submission!
04/2023: Sian Jin has received five assistant professor offers from U.S. R1 universities, including Binghamton, Temple, Colorado School of Mines, UKY, UNM. He will join Temple in Spring 2024. Huge congratulations to Sian!
04/2023: Three papers have been accepted for publication in ICS'23.
03/2023: One paper has been accepted for publication in HPDC'23.
12/2022: I receive the NSF CAREER Award! It is the NSF's most prestigious award in support of early-career faculty. Thanks a lot to NSF! [ Abstract ]
11/2022: One paper has been accepted for publication in AAAI'23.
11/2022: One paper has been accepted for publication in VLDB'23.
11/2022: One paper has been accepted for publication in PPoPP'23.
10/2022: Sian and Boyuan received SC'22 Student Travel Grants. Jiannan and Baixi received ACM SIGHPC Student Research Competition Travel Grants.
09/2022: We received the 2022 Meta Research Award on AI System Hardware/Software Codesign! Many thanks to Meta Research! [ Meta News ] [ IU News ]
08/2022: Our two proposals were selected as a finalist in Meta RFP - Networking for AI and AI System Hardware/Software Codesign.
08/2022: One paper has been accepted for publication in PACT'22.
07/2022: We presented our CSSI and CDS&E projects at 2022 NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) Principal Investigator Meeting at Alexandria, VA. [ CSSI-Poster ] [ CDS&E-Poster ]
07/2022: A 250k OAC Core project was funded by NSF (my role: site PI). Thanks a lot to NSF!
07/2022: I gave a talk on compression software fosr HPC storage and I/O at Watson Software Paper Bar. Thank you for Yuxin's invitation! It was fun! [ Slides ] [ Thank You Letter ]
07/2022: I gave a 3-hour talk at OxML Summer School Fundamental Sessions about ML Systems. [ Video ] [ Slides ]
06/2022: One paper has been accepted for publication in FPL'22.
06/2022: One paper has been accepted for publication in SC'22. Congratulations to Sian!
04/2022: Two papers have been accepted for publication in ICS'22.
04/2022: Two papers have been accepted for publication in HPDC'22.
03/2022: One paper has been accepted for publication in ICDE'22.
03/2022: I'll deliver a lecture at Oxford Machine Learning Summer School (OxML) for an ML Fundamentals module on June 27-29. Thanks for Yaodong's invitation!
02/2022: Congratulations to Cody being admitted by UIUC and Princeton CS PhD program!
02/2022: Our research has been featured again in the school's newsletter. [ News ]
02/2022: Chengming got a research internship offer from Microsoft Research to work with a DeepSpeed team on building massive-scale AI systems.
01/2022: Sian has been selected for PNNL-WSU Distinguished Graduate Research Program (DGRP) Fellowship.
12/2021: One paper has been accepted for publication in IEEE IPDPS'22.
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!
11/2021: One paper has been accepted for publication in VLDB'22.
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: A 280k CSSI project was funded by NSF (my role: site 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!
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
Quantum computing
SELECTED GRANTS
NSF, Single PI, CAREER: A Highly Effective, Usable, Performant, Scalable Data Reduction Framework for HPC Systems and Applications, $480K, 2023-2027. [ Abstract ]
NSF, Site PI, Collaborative Research: SHF: Small: Reimagining Communication Bottlenecks in GNN Acceleration through Collaborative Locality Enhancement and Compression Co-Design, $300K, 2023-2026. [ Abstract ]
NSF, Site PI, Collaborative Research: Frameworks: FZ: A fine-tunable cyberinfrastructure framework to streamline specialized lossy compression development, $580K, 2023-2027. [ Abstract ]
NSF, Site PI, OAC Core: CEAPA: A Systematic Approach to Minimize Compression Error Propagation in HPC Applications, $250K, 2022-2025. [ Abstract ]
NSF, Site PI, CSSI: Elements: ROCCI: Integrated Cyberinfrastructure for In Situ Lossy Compression Optimization Based on Post Hoc Analysis Requirements, $280K, 2021-2024. [ Abstract ]
NSF, Lead PI, CDS&E: HyLoC: Objective-driven Adaptive Hybrid Lossy Compression Framework for Extreme-Scale Scientific Applications, $270K, 2020-2023. [ Abstract ]
NSF, Single PI, 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
NSF CAREER Award, 2023
Amazon Research Award (ARA), 2022
Meta Research Award, 2022
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
Data Reduction for Floating-Point Data
Compression-supported HPC and Big Data Analytics
High-Performance Deep Learning Systems
High-Performance Scientific Computing
SOFTWARE
cuSZ: A GPU-accelerated Error-bounded Lossy Compressor for Scientific Data (https://github.com/szcompressor/cuSZ)
SZ: Error-bounded Lossy Compressor for HPC Data (https://github.com/szcompressor/SZ)
CEAZ: An Implementation of SZ Lossy Compression in Vivado HLS for Xilinx FPGAs (https://github.com/szcompressor/SZ_HLS)
DeepSZ: A Novel Framework to Compress DNNs by Using Error-bounded Lossy Compression (https://github.com/szcompressor/DeepSZ)
Z-checker: A Library to Assess Lossy Compression Quality (https://github.com/CODARcode/Z-checker)
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!
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
IU ENGR 516 - Engineering Cloud Computing [Fall 2022, Spring 2023]: This course covers basic concepts on programming models and tools of cloud computing to support data intensive science applications. Students will get to know the latest research topics of cloud platforms, parallel algorithms, storage and high level language for proficiency with a complex ecosystem of tools that span many disciplines.
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.
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'24
top-cs, top-cr
Xinyu Chen, Jiannan Tian, Ian Beaver, Cynthia Freeman, Yan Yan, Jianguo Wang, Dingwen Tao*.
FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data.
Proceedings of the 50th International Conference on Very Large Data Bases, Guangzhou, China, August 25-29, 2024. [ Paper ] [ Code ]
DAC'24
top-cs, top-cr
Chenxi Li, Boyuan Zhang, Yonggiang Duan, Yang Li, Zuochang Ye, Weifeng Liu, Dingwen Tao, Zhou Jin.
MASC: A Memory-Eficient Adjoint Sensitivity Analysis through Compression Using Novel Spatiotemporal Prediction
Proceedings of the 61st Annual Design Automation Conference, San Francisco, CA, USA, June 23-27, 2024. [ Paper ]
TPDS'24
top journal, impact factor: 4.181
Daoce Wang, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, Kai Zhao, James Arhens, and Dingwen Tao*.
TAC+: Optimizing Error-Bounded Lossy Compression for 3D AMR Simulations.
IEEE Transactions on Parallel and Distributed Systems. [ Paper ]
EUROSYS'24
top-cs, top-cr
Sian Jin, Sheng Di, Frédéric Vivien, Daoce Wang, Yves Robert, Dingwen Tao*, and Franck Cappello.
Concealing Compression-Accelerated I/O for HPC Applications through In Situ Task Scheduling.
Proceedings of the Nineteenth European Conference on Computer Systems, Athens, Greece, April 23-26, 2024. Acceptance Rate: 16% (39/244) [ Paper ] [ Code ]
DCC'24
top-cr
Yang Shi, Xiangyu Zou, Xinyu Chen, Sian Jin, Dingwen Tao, Cai Deng, Yufan Chen, and Wen Xia.
Machete: An Efficient Lossy Floating-Point Compressor Designed for Time Series Databases.
Proceedings of 2023 Data Compression Conference (DCC), Snowbird, UT, USA, March 19-22, 2024. [ Paper ] [ Code ]
SC'23
top-cs, top-cr
Daoce Wang, Jesus Pulido, Pascal Grosset, Jiannan Tian, Sian Jin, Houjun Tang, Jean Sexton, Sheng Di, Zarija Lukić, Kai Zhao, Bo Fang, Franck Cappello, James Ahrens, and Dingwen Tao*.
AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications.
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Denver, CO, USA, Nov 12-17, 2023. Acceptance Rate: 24% (90/376) [ Paper ] [ Slides ] [ Code ]
SC'23
top-cs, top-cr
Zhengyang He, Yafan Huang, Hui Xu, Dingwen Tao, Guanpeng Li.
Demystifying and Mitigating Cross-Layer Deficiencies of Soft Error Protection in Instruction Duplication.
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Denver, CO, USA, Nov 12-17, 2023. Acceptance Rate: 24% (90/376) [ Paper ] [ Code ]
ICS'23
top-cs, top-cr
Chengming Zhang, Shaden Smith, Baixi Sun, Jiannan Tian, Jonathan Soifer, Xiaodong Yu, Shuaiwen Song, Yuxiong He, and Dingwen Tao*.
HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs.
Proceedings of the 37th ACM International Conference on Supercomputing, Orlando, FL, USA, June 21-23, 2023. Acceptance Rate: 29% (40/136) [ Paper ] [ Slides ] [ Code ]
ICS'23
top-cs, top-cr
Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Martin Swany, Dingwen Tao*, Franck Cappello.
gpuLZ: Optimizing LZSS Lossless Compression for Multi-byte Data on Modern GPUs.
Proceedings of the 37th ACM International Conference on Supercomputing, Orlando, FL, USA, June 21-23, 2023. Acceptance Rate: 29% (40/136) [ Paper ] [ Slides ] [ Code ]
ICS'23
top-cs, top-cr
Anqi Guo, Yuchen Hao, Chunshu Wu, Pouya Haghi, Zhenyu Pan, Min Si, Dingwen Tao*, Ang Li, Martin Herbordt, Tong Geng.
Software-Hardware Co-design of Heterogeneous SmartNIC System for Recommendation Models Inference and Training.
Proceedings of the 37th ACM International Conference on Supercomputing, Orlando, FL, USA, June 21-23, 2023. Acceptance Rate: 29% (40/136) [ Paper ] [ Slides ]
HPDC'23
top-cs, top-cr
Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Yunhe Feng, Xin Liang, Dingwen Tao*, Franck Cappello.
FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs.
Proceedings of the 32nd ACM International Symposium on High-Performance Parallel and Distributed Computing, Orlando, Florida, June 16–23, 2023. Acceptance Rate: 21% (22/101). [ Paper ] [ Slides ] [ Code ]
TPDS'23
top journal, impact factor: 4.181
Haoyu Jin, Donglei Wu, Shuyu Zhang, Xiangyu Zou, Sian Jin, Dingwen Tao, Qing Liao, and Wen Xia.
Design of a Quantization-based DNN Delta Compression Framework for Model Snapshots and Federated Learning.
IEEE Transactions on Parallel and Distributed Systems. [ Paper ]
AAAI'23
top-cs, top-cr
Jinqi Xiao*, Chengming Zhang*, Yu Gong, Miao Yin, Yang Sui, Lizhi Xiang, Dingwen Tao, Bo Yuan.
HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks.
Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington DC, USA, February 7-14, 2023. Acceptance Rate: 19% (1721/8777) [ Paper ] [ Slides ] (*equal contribution)
VLDB'23
top-cs, top-cr
Pu Jiao, Sheng Di, Hanqi Guo, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang*, Franck Cappello.
Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data.
Proceedings of the 49th International Conference on Very Large Data Bases, Vancouver, Canada, August 28-September 1, 2023. [ Paper ]
PPOPP'23
top-cr
Lizhi Xiang*, Miao Yin*, Chengming Zhang, Aravind Sukumaran-Rajam, P. Saday, Bo Yuan, Dingwen Tao.
TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition.
Proceedings of the 28th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Montreal, Canada, February 25 - March 1, 2023. Acceptance Rate: 23% (31/131) [ Paper ] [ Slides ] (*equal contribution)
SC'22
top-cs, top-cr
Sian Jin, Dingwen Tao*, Houjun Tang, Sheng Di, Suren Byna, Zarija Lukic, and Franck Cappello.
Accelerating Parallel Write via Deeply Integrating Predictive Lossy Compression with HDF5.
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Dallas, TX, USA, Nov 13-18, 2022. Acceptance Rate: 24% (81/330) [ Paper ] [ Slides ] [ Talk ]
PACT'22
top-cr
Xinyu Chen, Marco Minutoli, Jiannan Tian, Mahantesh Halappanavar, Ananth Kalyanaraman, and Dingwen Tao*.
HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures.
Proceedings of the 31st ACM International Conference on Parallel Architectures and Compilation Techniques, Chicago, IL, USA, October 10-12, 2022. [ Paper ] [ Slides ] [ Poster ]
VLDB'22
top-cs, top-cr
Sian Jin, Chengming Zhang, Xintong Jiang, 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, Sydney, Australia, September 5-9, 2022. [ Paper ] [ Slides ] [ Poster ] [ Talk ]
TPDS'22
top journal, impact factor: 4.181
Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, and Franck Cappello.
Optimizing Error-Bounded Lossy Compression for Scientific Data with Diverse Constraints.
IEEE Transactions on Parallel and Distributed Systems. [ Paper ]
FPL'22
top-cr
Chengming Zhang, Tong Geng, Anqi Guo, Jiannan Tian, Martin Herbordt, Ang Li and Dingwen Tao*.
H-GCN: A Graph Convolutional Network Accelerator on Versal ACAP Architecture.
The 32nd International Conference on Field Programmable Logic and Applications, Belfast, UK, August 29-September 2, 2022. Acceptance Rate: 25% (33/129) [ Paper ] [ Slides ] { Talk ]
ICS'22
top-cs, top-cr
Chengming Zhang, Sian Jin, Tong Geng, Jiannan Tian, Ang Li, and Dingwen Tao*.
CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Designed Adaptive Lossy Compression.
Proceedings of the 36th ACM International Conference on Supercomputing, Virtual Event, USA, June 27-30, 2022. Acceptance Rate: 23% (39/165) [ Paper ] [ Slides ] [ Talk ]
ICS'22
top-cs, top-cr
Heng Zhang, Lingda Li, Hang Liu, Donglin Zhuang, Rui Liu, Chengying Huan, Shuang Song, Dingwen Tao, Yongchao Liu, Charles He, Yanjun Wu, and Shuaiwen Leon Song.
Bring Orders into Uncertainty: Enabling Efficient Uncertain Graph Processing via Novel Path Sampling on Multi-Accelerator System.
Proceedings of the 36th ACM International Conference on Supercomputing, Virtual Event, USA, June 27-30, 2022. Acceptance Rate: 23% (39/165) [ Paper ] [ Talk ]
HPDC'22
top-cs, top-cr
Daoce Wang, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, James Ahrens, and Dingwen Tao*.
TAC: Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations.
Proceedings of the 31st ACM International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, Minnesota, June 27-July 1, 2022. Acceptance Rate: 19% (21/108). [ Paper ] [ Slides ] [ Talk ]
HPDC'22
top-cs, top-cr
Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, and Franck Cappello.
Ultra-fast Error-bounded Lossy Compression for Scientific Dataset.
Proceedings of the 31st ACM International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, Minnesota, June 27-July 1, 2022. Acceptance Rate: 19% (21/108). [ Paper ]
ICDE'22
top-cs, top-cr
Sian Jin, Sheng Di, Jiannan Tian, Suren Byna, Dingwen Tao*, and Franck Cappello.
Improving Prediction-Based Lossy Compression Dramatically via Ratio-Quality Modeling.
Proceedings of the 38th IEEE International Conference on Data Engineering, Virtual Event, May 9-12, 2022. Acceptance Rate: 27% (211/780) [ Paper ] [ Slides ] [ Talk ]
IPDPS'22
top-cr
Cody Rivera, Sheng Di, Xiaoding Yu, Jiannan Tian, Dingwen Tao*, and Franck Cappello.
Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs.
Proceedings of the 36th IEEE International Parallel and Distributed Processing Symposium, Lyon, France, May 30-June 3, 2022. Acceptance Rate: 25% (123/474) [ Paper ] [ Slides ]
TC'21
top journal, impact factor: 3.131
Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, Dave Pugmire, Matthew Wolf, Nobert Podhorszki, and Scott Klasky.
MGARD+: Optimizing Multilevel Methods for Error-bounded Scientific Data Reduction.
IEEE Transactions on Computers 71, no. 7 (2021): 1522-1536. [ Paper ]
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, 2021. 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 ]
JPDC'21
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 ]
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 ]
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 ]
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 ]
TPDS'20
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 ]
TPDS'19
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 ]
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 ]
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 ]
TPDS'18
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 ]
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% (1/154) [ 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
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 ]
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 ]
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