| SZ3: A modular framework for composing prediction-based error-bounded lossy compressors X Liang, K Zhao, S Di, S Li, R Underwood, AM Gok, J Tian, J Deng, ... IEEE Transactions on Big Data, 2022 | 100 | 2022 |
| 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 | 91 | 2020 |
| Fraz: a generic high-fidelity fixed-ratio lossy compression framework for scientific floating-point data R Underwood, S Di, JC Calhoun, F Cappello 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2020 | 49 | 2020 |
| Measuring Network Latency Variation Impacts to High Performance Computing Application Performance R Underwood, J Anderson, A Apon Proceedings of the 2018 ACM/SPEC International Conference on Performance …, 2018 | 22 | 2018 |
| OptZConfig: Efficient Parallel Optimization of Lossy Compression Configuration R Underwood, JC Calhoun, S Di, A Apon, F Cappello IEEE Transactions on Parallel and Distributed Systems, 2022 | 18 | 2022 |
| Productive and Performant Generic Lossy Data Compression with LibPressio R Underwood, V Malvoso, JC Calhoun, S Di, F Cappello 2021 7th International Workshop on Data Analysis and Reduction for Big …, 2021 | 15 | 2021 |
| Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets D Krasowska, J Bessac, R Underwood, JC Calhoun, S Di, F Cappello 2021 7th International Workshop on Data Analysis and Reduction for Big …, 2021 | 11 | 2021 |
| ROIBIN-SZ: Fast and Science-Preserving Compression for Serial Crystallography R Underwood, C Yoon, A Gok, S Di, F Cappello arXiv preprint arXiv:2206.11297, 2022 | 10 | 2022 |
| Datastates-llm: Lazy asynchronous checkpointing for large language models A Maurya, R Underwood, MM Rafique, F Cappello, B Nicolae Proceedings of the 33rd International Symposium on High-Performance Parallel …, 2024 | 9 | 2024 |
| Black-box statistical prediction of lossy compression ratios for scientific data R Underwood, J Bessac, D Krasowska, JC Calhoun, S Di, F Cappello The International Journal of High Performance Computing Applications 37 (3-4 …, 2023 | 7 | 2023 |
| ARC: An Automated Approach to Resiliency for Lossy Compressed Data via Error Correcting Codes D Fulp, A Poulos, R Underwood, JC Calhoun Proceedings of the 30th International Symposium on High-Performance Parallel …, 2020 | 7 | 2020 |
| A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets MH Rahman, S Di, K Zhao, R Underwood, G Li, F Cappello 2023 IEEE 39th International Conference on Data Engineering (ICDE), 1461-1474, 2023 | 6 | 2023 |
| Understanding the Effects of Modern Compressors on the Community Earth Science Model R Underwood, J Bessac, S Di, F Cappello 2022 IEEE/ACM 8th International Workshop on Data Analysis and Reduction for …, 2022 | 6 | 2022 |
| DStore: A Lightweight Scalable Learning Model Repository with Fine-Grain Tensor-Level Access M Madhyastha, R Underwood, R Burns, B Nicolae Proceedings of the 37th International Conference on Supercomputing, 133-143, 2023 | 5 | 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 | 4 | 2024 |
| CliZ: Optimizing Lossy Compression for Climate Datasets with Adaptive Fine-tuned Data Prediction Z Jian, S Di, J Liu, K Zhao, X Liang, H Xu, R Underwood, S Wu, J Huang, ... 2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2024 | 3 | 2024 |
| Efficient Communication in Federated Learning Using Floating-Point Lossy Compression G Wilkins, S Di, JC Calhoun, K Kim, R Underwood, F Cappello arXiv preprint arXiv:2312.13461, 2023 | 3 | 2023 |
| Understanding The Effectiveness of Lossy Compression in Machine Learning Training Sets R Underwood, JC Calhoun, S Di, F Cappello arXiv preprint arXiv:2403.15953, 2024 | 2 | 2024 |
| Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing F Cappello, M Acosta, E Agullo, H Anzt, J Calhoun, S Di, L Giraud, ... Future Generation Computer Systems 163, 107323, 2025 | 1 | 2025 |
| FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications G Wilkins, S Di, JC Calhoun, Z Li, K Kim, R Underwood, R Mortier, ... 2024 IEEE 44th International Conference on Distributed Computing Systems …, 2024 | 1 | 2024 |
Sheng DiArgonne National Labratory, IEEE Senior MemberEmail verificata su anl.gov
