PacificVis'20

Xin Liang, Hanqi Guo, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen and Tom Peterka.
Towards Feature Preserving 2D and 3D Vector Field Compression.
Accepted in the 13rd IEEE Pacific Visualization Symposium, Tianjin, China, Apr 14-17, 2020.

SC'19

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: 20.9% (72/344)

SC'19

Sihuan Li, Hongbo Li, Xin Liang, Jieyang Chen, Elisabeth Giem, Kaiming Ouyang, Kai Zhao, Sheng Di, Franck Cappello, and Zizhong Chen.
FT-iSort: Efficient Fault Tolerance for Introsort.
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: 20.9% (72/344)

Cluster'19

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: 27.7% (39/141)

HPDC'19

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: 20.7% (22/106)

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: 18.9% (98/518)

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 (best paper award in Data, Storage, and Visualization Area).
Proceedings of the 2018 IEEE International Conference on Cluster Computing, Belfast, UK, September 10 - 13, 2018. Less than 2.6% (4/154) of submissions are awarded best papers.

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)

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)

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).

IPDPS'16

Jieyang Chen, Xin Liang, and Zizhong Chen.
Online Algorithm-Based Fault Tolerance for Cholesky Decomposition on Heterogeneous Systems with GPUs.
Proceedings of the 30th IEEE International Parallel & Distributed Processing Symposium, Chicago, Illinois, USA, May 23-27, 2016. Acceptance Rate: 22.98% (114/496)