High-performance computing (HPC), parallel algorithms and software, distributed machine learning systems, scientific data management and storage, data compression.

• 2013–2018 | Ph.D. in Computer Science, University of California, Riverside, USA
• 2009–2013 | B.S. in Computer Science, University of Science and Technology of China (USTC)

• 2024–Present | Professor, ICT-CAS, China
• 2022–2024 | Associate Professor, Indiana University, USA
• 2020–2022 | Assistant Professor, Washington State University, USA
• 2018–2020 | Assistant Professor, University of Alabama, USA
• 2018 | Research Assistant, Brookhaven National Lab, USA
• 2016–2017 | Research Assistant, Argonne National Lab, USA
• 2015 | Ph.D. Intern, Pacific Northwest National Lab, USA

Conference Publications

1. Boyuan Zhang, Bo Fang, Fanjiang Ye, Luanzheng Guo, Tallent Nathan, Dingwen Tao. "BMQSim: Overcoming Memory Constraints in Quantum Circuit Simulation with a High-Fidelity Compression Framework."  The 39th ACM International Conference on Supercomputing, Salt Lake City, UT, USA, June 8–11, 2025.

2. Chenxi Li, Yihang Feng, Fuxing Deng, Dingwen Tao, Weifeng Liu, Zhou Jin. "MemSens: Significantly Reducing Memory Overhead in Adjoint Sensitivity Analysis Using Novel Error-Bounded Lossy Compression." The 62nd Annual Design Automation Conference, San Francisco, CA, USA, June 22–25, 2025.

3. Donglei Wu, Weihao Yang, Xiangyu Zou, Jinda Jia, Dingwen Tao, Wen Xia, Zhihong Tian. "BirdMoE: Reducing Communication Costs for Mixture-of-Experts Training Using Load-Aware Bi-random Quantization." The 62nd Annual Design Automation Conference, San Francisco, CA, USA, June 22–25, 2025.

4. Jinda Jia, Cong Xie, Hanlin Lu, Daoce Wang, Hao Feng, Chengming Zhang, Baixi Sun, Haibin Lin, Zhi Zhang, Xin Liu, Dingwen Tao. "SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training." Advances in Neural Information Processing Systems 37 (2025).

5. Hao Hu, Qiyang Zheng, Xiangyu Zou, Lisha Qin, Chengwei Zhang, Wanchuan Zhang, Zhaoheng Jiang, Daoce Wang, Dingwen Tao, Hongpeng Wang, Wen Xia. "A Cost-Effective and Decompression-Transparent Compressor for OLTP-Oriented Databases." The 41st IEEE International Conference on Data Engineering, Hong Kong SAR, May 19–23, 2025.

6. Longtao Zhang, Ruoyu Li, Congrong Ren, Sheng Di, Jinyang Liu, Jiajun Huang, Robert Underwood, Pascal Grosset, Dingwen Tao, Xin Liang, Hanqi Guo, Franck Cappello, Kai Zhao. "LCP: Enhancing Scientific Data Management with Lossy Compression for Particles." Proceedings of the ACM on Management of Data, Berlin, Germany, June 22-27, 2025.

7. Baixi Sun, Weijin Liu, J. Gregory Pauloski, Jiannan Tian, Jinda Jia, Daoce Wang, Mingkai Zheng, Sheng Di, Sian Jin, Zhao Zhang, Xiaodong Yu, Guangming Tan, Dingwen Tao. "COMPSO: Optimizing Gradient Compression for Distributed Training with Second-Order Optimizers." The 28th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Las Vegas, Nevada, March 1–March 5, 2025.

8. Hao Feng, Boyuan Zhang, Fanjiang Ye, Min Si, Ching-Hsiang Chu, Jiannan Tian, Chunxing Yin, Zhaoxia (Summer) Deng, Yuchen Hao, Pavan Balaji, Tong Geng, Dingwen Tao. "Accelerating Communication in Deep Learning Recommendation Model Training with Dual-Level Adaptive Lossy Compression." SC24: The International Conference for High Performance Computing, Networking, Storage and Analysis, Atlanta, GA, USA, November 17–22, 2024.

9. Daoce Wang, Pascal Grosset, Jesus Pulido, Tushar M. Athawale, Jiannan Tian, Kai Zhao, Zarija Lukic, Axel Huebl, Zhe Wang, James Ahrens, Dingwen Tao. "A High-Quality Workflow for Multi-Resolution Scientific Data Reduction and Visualization." SC24: The International Conference for High Performance Computing, Networking, Storage and Analysis, Atlanta, GA, USA, November 17–22, 2024.

10. Jinyang Liu, Jiannan Tian, Shixun Wu, Sheng Di, Boyuan Zhang, Robert Underwood, Yafan Huang, Jiajun Huang, Kai Zhao, Guanpeng Li, Dingwen Tao, Zizhong Chen, and Franck Cappello. "CUSZ-i: High-Ratio Scientific Lossy Compression on GPUs with Optimized Multi-Level Interpolation." SC24: The International Conference for High Performance Computing, Networking, Storage and Analysis, Atlanta, GA, USA, November 17–22, 2024.

11. Zhen Xie, Murali Emani, Xiaodong Yu, Dingwen Tao, Xin He, Pengfei Su, Keren Zhou, Venkatram Vishwanath. "Centimani: Enabling Fast AI Accelerator Selection for DNN Training with a Novel Performance Predictor." 2024 USENIX Annual Technical Conference, Santa Clara, CA, USA, July 10-12, 2024.

12. 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." The 50th International Conference on Very Large Data Bases, Guangzhou, China, August 25-29, 2024. DOI: 10.14778/3648160.3648180.

13. 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." The 61st Annual Design Automation Conference, San Francisco, CA, USA, June 23–27, 2024. DOI: 10.1145/3649329.3657393.

14. Sian Jin, Sheng Di, Frederic Vivien, Daoce Wang, Yves Robert, Dingwen Tao, Franck Cappello. "Concealing Compression-Accelerated I/O for HPC Applications through In Situ Task Scheduling." The Nineteenth European Conference on Computer Systems, Athens, Greece, April 23-26, 2024. DOI: 10.1145/3627703.3629573.

15. Daoce Wang, Jesus Pulido, Pascal Grosset, Jiannan Tian, Sian Jin, Houjun Tang, Jean Sexton, Sheng Di, Zarija Lukic, Kai Zhao, Bo Fang, Franck Cappello, James Ahrens, Dingwen Tao. "AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications." SC23: The International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, USA, November 12–17, 2023. DOI: 10.1145/3581784.3613212.

16. Zhengyang He, Yafan Huang, Hui Xu, Dingwen Tao, Guanpeng Li. "Demystifying and Mitigating Cross-Layer Deficiencies of Soft Error Protection in Instruction Duplication." SC23: The International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, USA, November 12–17, 2023. DOI: 10.1145/3581784.3607078.

17. Chengming Zhang, Shaden Smith, Baixi Sun, Jiannan Tian, Jonathan Soifer, Xiaodong Yu, Shuaiwen Song, Yuxiong He, Dingwen Tao. "HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs." The 37th ACM International Conference on Supercomputing, Orlando, FL, USA, June 21–23, 2023. DOI: 10.1145/3577193.3593717.

18. 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." The 37th ACM International Conference on Supercomputing, Orlando, FL, USA, June 21–23, 2023. DOI: 10.1145/3577193.3593706.

19. 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." The 37th ACM International Conference on Supercomputing, Orlando, FL, USA, June 21–23, 2023. DOI: 10.1145/3577193.3593724.

20. 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." The 32nd ACM International Symposium on High-Performance Parallel and Distributed Computing, Orlando, FL, June 16–23, 2023. DOI: 10.1145/3588195.3592994.

21. 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." The 49th International Conference on Very Large Data Bases, Vancouver, Canada, August 28–September 1, 2023. DOI: 10.14778/3574245.3574255.

22. 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." The 37th AAAI Conference on Artificial Intelligence, Washington, DC, USA, Feb 7–14, 2023. DOI: 10.1609/aaai.v37i9.26244.

23. 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." The 28th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Montreal, Canada, Feb 26–March 1, 2023. DOI: 10.1145/3572848.3577478.

24. Sian Jin, Dingwen Tao, Houjun Tang, Sheng Di, Suren Byna, Zarija Lukic, Franck Cappello. "Accelerating Parallel Write via Deeply Integrating Predictive Lossy Compression with HDF5." SC22: The International Conference for High Performance Computing, Networking, Storage and Analysis, Dallas, TX, USA, November 13–18, 2022. DOI: 10.1109/SC41404.2022.00066.

25. Chengming Zhang, Sian Jin, Tong Geng, Jiannan Tian, Ang Li, Dingwen Tao. "CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Designed Adaptive Lossy Compression." The 36th ACM International Conference on Supercomputing, Virtual, USA, June 27–30, 2022. DOI: 10.1145/3524059.3532362.

26. Heng Zhang, Lingda Li, Hang Liu, Donglin Zhuang, Rui Liu, Chengying Huan, Shuang Song, Dingwen Tao, Yongchao Liu, Charles He, Yanjun Wu, Shuaiwen Leon Song. "Bring Orders into Uncertainty: Enabling Efficient Uncertain Graph Processing via Novel Path Sampling on Multi-Accelerator System." The 36th ACM International Conference on Supercomputing, Virtual, USA, June 27–30, 2022. DOI: 10.1145/3524059.3532379.

27. Daoce Wang, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, James Ahrens, Dingwen Tao. "TAC: Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations." The 31st ACM International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, MN, June 27–July 1, 2022. DOI: 10.1145/3502181.3531458.

28. Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello. "Ultra-fast Error-bounded Lossy Compression for Scientific Dataset." The 31st ACM International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, MN, June 27–July 1, 2022. DOI: 10.1145/3502181.3531473.

29. Sian Jin, Sheng Di, Jiannan Tian, Suren Byna, Dingwen Tao, Franck Cappello. "Improving Prediction-Based Lossy Compression Dramatically via Ratio-Quality Modeling." The 38th IEEE International Conference on Data Engineering, Virtual Event, May 9–12, 2022. DOI: 10.1109/ICDE53745.2022.00232.

30. 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." The 48th International Conference on Very Large Data Bases, Australia, September 5–9, 2022. DOI: 10.14778/3503585.3503597.

31. Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Song, Dingwen Tao. "ClickTrain: Efficient and Accurate End-to-End Deep Learning Training via Fine-Grained Architecture-Preserving Pruning." The 35th ACM International Conference on Supercomputing, Virtual, USA, June 14–17, 2021. DOI: 10.1145/3447818.3459988.

32. Sian Jin, Jesus Pulido, Pascal Grosset, Jiannan Tian, Dingwen Tao, James Ahrens. "Adaptive Configuration of In Situ Lossy Compression for Cosmology Simulations via Fine-Grained Rate-Quality Modeling." The 30th ACM International Symposium on High-Performance Parallel and Distributed Computing, Virtual Event, Sweden, June 21–25, 2021. DOI: 10.1145/3431379.3460653.

33. Peiyan Dong, Siyue Wang, Wei Niu, Chengming Zhang, Sheng Lin, Zhengang Li, Yifan Gong, Bin Ren, Xue Lin, Dingwen Tao. "RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition." The 57th Annual Design Automation Conference, San Francisco, CA, USA, July 19–23, 2020. DOI: 10.5555/3437539.3437579.

34. Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Zizhong Chen, Franck Cappello. "Significantly Improving Lossy Compression for HPC Datasets with Second-Order Prediction and Parameter Optimization." The 29th ACM International Symposium on High-Performance Parallel and Distributed Computing, Stockholm, Sweden, June 23–26, 2020. DOI: 10.1145/3369583.3392688.

35. Jiannan Tian, Sheng Di, Chengming Zhang, Xin Liang, Sian Jin, Dazhao Cheng, Dingwen Tao, Franck Cappello. "waveSZ: A Hardware-Algorithm Co-Design of Efficient Lossy Compression for Scientific Data." The 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, San Diego, CA, USA, Feb 22–26, 2020. DOI: 10.1145/3332466.3374525.

36. Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao, Franck Cappello. "DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression." The 28th ACM International Symposium on High-Performance Parallel and Distributed Computing, Phoenix, AZ, USA, June 24–28, 2019. DOI: 10.1145/3307681.3326608.

37. Xin Liang, Sheng Di, Sihuan Li, Dingwen Tao, Bogdan Nicolae, Zizhong Chen, Franck Cappello. "Significantly Improving Lossy Compression Quality Based on An Optimized Hybrid Prediction Model." SC19: The International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, USA, Nov 17–22, 2019. DOI: 10.1145/3295500.3356193.

38. Jieyang Chen, Nan Xiong, Xin Liang, Dingwen Tao, Sihuan Li, Kaiming Ouyang, Kai Zhao, Nathan DeBardeleben, Qiang Guan, Zizhong Chen. "TSM2: Optimizing Tall-and-Skinny Matrix-Matrix Multiplication on GPUs." The 33rd ACM International Conference on Supercomputing, AZ, USA, June 26–28, 2019. DOI: 10.1145/3330345.3330355.

39. Jieyang Chen, Hongbo Li, Sihuan Li, Xin Liang, Panruo Wu, Dingwen Tao, Kaiming Ouyang, Yuanlai Liu, Kai Zhao, Qiang Guan, Zizhong Chen. "FT-MAGMA: Fault Tolerance Dense Matrix Decomposition on Heterogeneous Systems with GPUs." SC18: The International Conference for High Performance Computing, Networking, Storage and Analysis, Dallas, TX, USA, Nov 11–16, 2018. DOI: 10.1109/SC.2018.00071.

40. Xin Liang, Sheng Di, Dingwen Tao, Zizhong Chen, Franck Cappello. "An Efficient Transformation Scheme for Lossy Data Compression with Point-wise Relative Error Bound." IEEE International Conference on Cluster Computing, Belfast, UK, September 10–13, 2018. DOI: 10.1109/CLUSTER.2018.00036. (Best Paper Award, 4/154).

41. Ali Murat Gok, Sheng Di, Yury Alexeev, Dingwen Tao, Vladimir Mironov, Franck Cappello. "PaSTRI: Error-Bounded Lossy Compression for Two-Electron Integrals in Quantum Chemistry." IEEE International Conference on Cluster Computing, Belfast, UK, September 10–13, 2018. DOI: 10.1109/CLUSTER.2018.00013. (Best Area Paper Award, 1/154)

42. Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, Franck Cappello. "Improving Performance of Iterative Methods by Lossy Checkponting." The 27th ACM International Symposium on High-Performance Parallel and Distributed Computing, Tempe, AZ, USA, June 11– 15, 2018. DOI: 10.1145/3208040.3208050.

43. Xin Liang, Jieyang Chen, Dingwen Tao, Sihuan Li, Panruo Wu, Hongbo Li, Kaiming Ouyang, Yuanlai Liu, Fengguang Song, Zizhong Chen. "Correcting Soft Errors Online in Fast Fourier Transform." SC17: The International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, USA, Nov 12–17, 2017. DOI: 10.1145/3126908.3126915.

44. Panruo Wu, Nathan Debardeleben, Qiang Guan, Sean Blanchard, Jieyang Chen, Dingwen Tao, Xin Liang, Kaiming Ouyang, Sihuan Li, Zizhong Chen. "Silent Data Corruption Resilient Two-sided Matrix Factorizations." The 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Austin, TX, USA, February 4–8, 2017. DOI: 10.1145/3155284.3018750.

45. Jieyang Chen, Li Tan, Panruo Wu, Dingwen Tao, Hongbo Li, Xin Liang, Sihuan Li, Rong Ge, Laxmi Bhuyan, Zizhong Chen. "GreenLA: Green Linear Algebra Software for GPU-Accelerated Heterogeneous Computing." SC16: The International Conference for High Performance Computing, Networking, Storage and Analysis, Salt Lake City, UT, USA. DOI: 10.1109/SC.2016.56.

46. Dingwen Tao, Shuaiwen Leon Song, Sriram Krishnamoorthy, Panruo Wu, Xin Liang, Eddy Z. Zhang, Darren Kerbyson, Zizhong Chen. "New-Sum: A Novel Online ABFT Scheme for General Iterative Methods." The 25th ACM International Symposium on High-Performance Parallel and Distributed Computing, Kyoto, JAPAN, May 31– June 4, 2016. DOI: 10.1145/2907294.2907306.

47. Panruo Wu, Qiang Guan, Nathan DeBardeleben, Sean Blanchard, Dingwen Tao, Xin Liang, Jieyang Chen, Zizhong Chen. "Towards Practical Algorithm Based Fault Tolerance in Dense Linear Algebra." The 25th ACM International Symposium on High-Performance Parallel and Distributed Computing, Kyoto, JAPAN, May 31–June 4, 2016. DOI: 10.1145/2907294.2907315.

Journal Publications

1. Donglei Wu, Weihao Yang, Xiangyu Zou, Hao Feng, Dingwen Tao, Shiyi Li, Wen Xia, Binxing Fang. “BIRD+: Design of a Lightweight Communication Compressor for Resource-Constrained Distribution Learning Platforms.” IEEE Transactions on Parallel and Distributed Systems 35, no. 11 (2024): 2193-2207. DOI: 10.1109/TPDS.2024.3447221.

2. Daoce Wang, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, Kai Zhao, James Arhens, Dingwen Tao. "TAC+: Optimizing Error-Bounded Lossy Compression for 3D AMR Simulations." IEEE Transactions on Parallel and Distributed Systems 35, no. 3 (2024): 421-438. DOI: 10.1109/TPDS.2023.3339474.

3. Xin Liang, Kai Zhao, Sheng Di, Sihuan Li, Robert Underwood, Ali Murat Gok, Jiannan Tian, Junjing Deng, Jon C. Calhoun, Dingwen Tao, Zizhong Chen, Franck Cappello: SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors. IEEE Transactions on Big Data 9, no. 2 (2023): 485-498. DOI: 10.1109/TBDATA.2022.3201176.（2023 Best Paper Award）

4. Haoyu Jin, Donglei Wu, Shuyu Zhang, Xiangyu Zou, Sian Jin, Dingwen Tao, Qing Liao, Wen Xia. "Design of a Quantization-based DNN Delta Compression Framework for Model Snapshots and Federated Learning." IEEE Transactions on Parallel and Distributed Systems 34, no. 3 (2023): 923-937. DOI: 10.1109/TPDS.2022.3230840.

5. Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, Franck Cappello. "Optimizing Error-Bounded Lossy Compression for Scientific Data with Diverse Constraints." IEEE Transactions on Parallel and Distributed Systems 33, no. 12 (2022): 4440-4457. DOI: 10.1109/TPDS.2022.3194695.

6. Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, Dave Pugmire, Matthew Wolf, Nobert Podhorszki, Scott Klasky. "MGARD+: Optimizing Multilevel Methods for Error-bounded Scientific Data Reduction." IEEE Transactions on Computers 71, no. 7 (2021): 1522-1536. DOI: 10.1109/TC.2021.3092201.

7. Xiangyu Zou, Tao Lu, Wen Xia, Xuan Wang, Weizhe Zhang, Haijun Zhang, Sheng Di, Dingwen Tao, 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. DOI: 10.1109/TPDS.2020.2972548.

8. Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, 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. DOI: 10.1109/TPDS.2019.2894404.

9. Sheng Di, Dingwen Tao, Xin Liang, 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. DOI: 10.1109/TPDS.2018.2859932.（CCF A类）

Current Projects

• Single PI, Key Foundational Software for Next-Generation Supercomputing, National Science Foundation of China, ￥27M, 2025–2030.
• Single PI, High-Performance Data Reduction Techniques for Extreme-Scale Cosmological Simulations, Chinese Academy of Sciences Collaboration Program, ￥800K, 2025–2027.
• Single PI, NPU Streaming Compression Technology Collaborative Project, Huawei Collaboration Program, ￥1.8M, 2025–2026.
• Single PI, Optimizing Communication Efficiency of Training Large Language Models via Adaptive Hybrid Compression, Huawei Collaboration Program, ￥1M, 2024–2025.
• Single PI, Fully Automated Parallelization and Heterogeneous Task Overlapping for Complex Model Training Scenarios, CCF-Baidu Funding Program, ￥100K, 2024–2025.
• Single PI, Efficient Compression Techniques for Large-Scale Model Pre-Training Communication Acceleration, Ant Research Program, ￥500K, 2024–2025.
• Single PI, Data Clustering and Grouped Compression Optimization Research, CCF-Guanghe Funding Program, ￥600K, 2024–2025.
• Single PI, Fundamental Software for High-Performance Computing, National Science Foundation of China, ￥2M, 2024–2027.
• Single PI, Data Reduction Methods for Intelligent Scientific Workflows, ICT-CAS Seed Funding, ￥2M, 2024–2026.

Past Projects

• Single PI, CAREER: A Highly Effective, Usable, Performant, Scalable Data Reduction Framework for HPC Systems and Applications, $480K, 2023–2024.

• Site PI, Collaborative Research: SHF: Small: Reimagining Communication Bottlenecks in GNN Acceleration through Collaborative Locality Enhancement and Compression Co-Design, $300K, 2023–2024.

• Site PI, Collaborative Research: Frameworks: FZ: A Fine-Tunable Cyberinfrastructure Framework to Streamline Specialized Lossy Compression Development, $580K, 2023–2024.

• Site PI, OAC Core: CEAPA: A Systematic Approach to Minimize Compression Error Propagation in HPC Applications, $250K, 2022–2024.

• Site PI, CSSI: Elements: ROCCI: Integrated Cyberinfrastructure for In Situ Lossy Compression Optimization Based on Post Hoc Analysis Requirements, $280K, 2021–2024.

• Lead PI, CDS&E: HyLoC: Objective-driven Adaptive Hybrid Lossy Compression Framework for Extreme-Scale Scientific Applications, $270K, 2020–2024.

• 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.

现指导学生

黄雯静  硕士研究生  081200-计算机科学与技术  

• CCF HPC "Young Talent in Science & Technology" Award, 2024
• NSF CAREER Award, 2023
• Meta Research Award, 2022
• R&D 100 Award, 2021
• IEEE CS TCHPC Early Career Researchers Award, 2020
• IEEE Cluster Best Paper Award, 2018
• University of California-Riverside (UCR) Dissertation Award, 2018