| 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 | 98 | 2020 |
| 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 | 82 | 2019 |
| 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 | 60 | 2021 |
| 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 | 46 | 2020 |
| 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 | 31 | 2020 |
| 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 | 30 | 2021 |
| 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 | 26 | 2022 |
| 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 | 26 | 2021 |
| 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 | 21 | 2023 |
| 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 | 18 | 2022 |
| 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 35th ACM International Conference on Supercomputing, 266-278, 2021 | 18 | 2021 |
| 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 | 16 | 2024 |
| 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 | 15 | 2020 |
| 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 | 14 | 2021 |
| 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 | 14 | 2021 |
| Pascal Grosset, Christopher M Biwer, Jesus Pulido, Jiannan Tian, Dingwen Tao, and James Ahrens. Understanding gpu-based lossy compression for extreme-scale cosmological simulations S Jin 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2020 | 12 | 2020 |
| 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 | 11 | 2023 |
| A survey on error-bounded lossy compression for scientific datasets S Di, J Liu, K Zhao, X Liang, R Underwood, Z Zhang, M Shah, Y Huang, ... arXiv preprint arXiv:2404.02840, 2024 | 10 | 2024 |
| 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 | 10 | 2022 |
| 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 | 10 | 2020 |
Dingwen TaoChinese Academy of Sciences, IEEE/ACM Senior MemberAdresă de e-mail confirmată pe ict.ac.cn