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Sian Jin
Sian Jin
在 temple.edu 的电子邮件经过验证 - 首页
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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
802020
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
722019
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
432021
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
432020
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
282020
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
252021
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
222022
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
202021
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
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
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
142022
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
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
132021
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
122023
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
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
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
82022
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
72022
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
Proceedings of the Nineteenth European Conference on Computer Systems, 981-998, 2024
62024
High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation
J Liu, S Di, K Zhao, X Liang, S Jin, Z Jian, J Huang, S Wu, Z Chen, ...
Proceedings of the ACM on Management of Data 2 (1), 1-27, 2024
52024
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