Jiannan Tian is currently Ph.D. Student at Indiana University ( jti1 'at' iu.edu ). His research interests include High-Performance Computing, Big-Data Analytics, heterogeneous computing, and Lossy Compression for Scientific Data. During his ongoing Ph.D. study, he works as a student intern at Argonne National Laboratory (ANL). He is also the main developer of open-source cuSZ, a GPU-accelerated error-bounded lossy compressor for scientific data.
[CLUSTER '21] 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, (Virtual Event) Portland, OR, September 7–10, 2021.
[IPDPS '21] Jiannan Tian, Cody Rivera, Jieyang Chen, Dingwen Tao, Sheng Di, and Franck Cappello. “Revisiting Huff- man Coding: Toward Extreme Performance on Modern GPU Architectures.” IEEE International Parallel & Distributed Processing Symposium, (Virtual Event) Portland, OR, May 17–21, 2021.
[PACT '20] Jiannan Tian, Sheng Di, Kai Zhao, Cody Rivera, Megan Hickman Fulp, Robert Underwood, Sian Jin, Xin Liang, Jon Calhoun, Dingwen Tao, and Franck Cappello. “cuSZ: A High-Performance GPU Based Lossy Compression Framework for Scientific Data.” The 29th International Conference on Parallel Architectures and Compilation Techniques, (Virtual Event) Atlanta, GA, October 3–7 2020.
[PPoPP '20] 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, CA, February 22–26, 2020.
[IPDPS ’23] (in submission) Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Dingwen Tao, and Franck Cappello.
[PPoPP ’23] (to resubmit) Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Lizhi Xiang, Dingwen Tao, and Franck Cappello.
[MASCOTS ’22] Griffin Dube, Jiannan Tian, Sheng Di, Dingwen Tao, Jon C. Calhoun, and Franck Cappello. “Efficient Error-Bounded Lossy Compression for CPU Architectures.” 30th International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, Nice, France, October 18–20, 2022.