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Sian Jin
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Cusz: An efficient gpu-based error-bounded lossy compression framework for scientific data
J Tian, S Di, K Zhao, C Rivera, MH Fulp, R Underwood, S Jin, X Liang, ...
Proceedings of the ACM International Conference on Parallel Architectures …, 2020
732020
DeepSZ: A novel framework to compress deep neural networks by using error-bounded lossy compression
S Jin, S Di, X Liang, J Tian, D Tao, F Cappello
Proceedings of the 28th international symposium on high-performance parallel …, 2019
702019
Understanding GPU-based lossy compression for extreme-scale cosmological simulations
S Jin, P Grosset, CM Biwer, J Pulido, J Tian, D Tao, J Ahrens
2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2020
402020
Exploring autoencoder-based error-bounded compression for scientific data
J Liu, S Di, K Zhao, S Jin, D Tao, X Liang, Z Chen, F Cappello
2021 IEEE International Conference on Cluster Computing (CLUSTER), 294-306, 2021
362021
Wavesz: A hardware-algorithm co-design of efficient lossy compression for scientific data
J Tian, S Di, C Zhang, X Liang, S Jin, D Cheng, D Tao, F Cappello
Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of …, 2020
262020
Optimizing error-bounded lossy compression for scientific data on gpus
J Tian, S Di, X Yu, C Rivera, K Zhao, S Jin, Y Feng, X Liang, D Tao, ...
2021 IEEE International Conference on Cluster Computing (CLUSTER), 283-293, 2021
232021
Improving prediction-based lossy compression dramatically via ratio-quality modeling
S Jin, S Di, J Tian, S Byna, D Tao, F Cappello
2022 IEEE 38th International Conference on Data Engineering (ICDE), 2494-2507, 2022
212022
Pascal Grosset, Christopher M Biwer, Jesus Pulido, Jiannan Tian, Dingwen Tao, and James Ahrens. 2020. Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological …
S Jin
arXiv preprint arXiv:2004.00224, 2020
202020
Comet: a novel memory-efficient deep learning training framework by using error-bounded lossy compression
S Jin, C Zhang, X Jiang, Y Feng, H Guan, G Li, SL Song, D Tao
arXiv preprint arXiv:2111.09562, 2021
182021
Clicktrain: Efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning
C Zhang, G Yuan, W Niu, J Tian, S Jin, D Zhuang, Z Jiang, Y Wang, B Ren, ...
Proceedings of the ACM international conference on supercomputing, 266-278, 2021
172021
Delta-DNN: Efficiently compressing deep neural networks via exploiting floats similarity
Z Hu, X Zou, W Xia, S Jin, D Tao, Y Liu, W Zhang, Z Zhang
Proceedings of the 49th International Conference on Parallel Processing, 1-12, 2020
142020
Accelerating parallel write via deeply integrating predictive lossy compression with HDF5
S Jin, D Tao, H Tang, S Di, S Byna, Z Lukic, F Cappello
SC22: International Conference for High Performance Computing, Networking …, 2022
122022
Adaptive configuration of in situ lossy compression for cosmology simulations via fine-grained rate-quality modeling
S Jin, J Pulido, P Grosset, J Tian, D Tao, J Ahrens
Proceedings of the 30th International Symposium on High-Performance Parallel …, 2021
122021
A novel memory-efficient deep learning training framework via error-bounded lossy compression
S Jin, G Li, SL Song, D Tao
Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of …, 2021
122021
Pascal Grosset, Jiannan Tian, Dingwen Tao, and James Ahrens. 2021. Adaptive configuration of in situ lossy compression for cosmology simulations via fine-grained rate-quality …
S Jin, J Pulido
arXiv preprint arXiv:2104.00178, 2021
102021
Design of a quantization-based dnn delta compression framework for model snapshots and federated learning
H Jin, D Wu, S Zhang, X Zou, S Jin, D Tao, Q Liao, W Xia
IEEE Transactions on Parallel and Distributed Systems 34 (3), 923-937, 2023
82023
Concealing compression-accelerated i/o for hpc applications through in situ task scheduling
S Jin, S Di, F Vivien, D Wang, Y Robert, D Tao, F Cappello
EuroSys 2024, 2024
72024
Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints
Y Liu, S Di, K Zhao, S Jin, C Wang, K Chard, D Tao, I Foster, F Cappello
IEEE Transactions on Parallel and Distributed Systems 33 (12), 4440-4457, 2022
72022
Ceaz: accelerating parallel i/o via hardware-algorithm co-designed adaptive lossy compression
C Zhang, S Jin, T Geng, J Tian, A Li, D Tao
Proceedings of the 36th ACM International Conference on Supercomputing, 1-13, 2022
62022
Amric: A novel in situ lossy compression framework for efficient i/o in adaptive mesh refinement applications
D Wang, J Pulido, P Grosset, J Tian, S Jin, H Tang, J Sexton, S Di, K Zhao, ...
Proceedings of the International Conference for High Performance Computing …, 2023
52023
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