| Error-controlled lossy compression optimized for high compression ratios of scientific datasets X Liang, S Di, D Tao, S Li, S Li, H Guo, Z Chen, F Cappello 2018 IEEE International Conference on Big Data (Big Data), 438-447, 2018 | 259 | 2018 |
| Vapor: A visualization package tailored to analyze simulation data in earth system science S Li, S Jaroszynski, S Pearse, L Orf, J Clyne Atmosphere 10 (9), 488, 2019 | 114 | 2019 |
| Data Reduction Techniques for Simulation, Visualization, and Data Analysis S Li, N Marsaglia, C Garth, J Woodring, J Clyne, H Childs Computer Graphics Forum, 2018 | 102 | 2018 |
| Toward a Multi-method Approach: Lossy Data Compression for Climate Simulation Data A Baker, H Xu, D Hammerling, S Li, J Clyne The 1st International Workshop on Data Reduction for Big Scientific Data …, 2017 | 56 | 2017 |
| Evaluating the Efficacy of Wavelet Configurations on Turbulent-Flow Data S Li, K Gruchalla, K Potter, J Clyne, H Childs IEEE Symposium on Large Data Analysis and Visualization (LDAV), 81--89, 2015 | 33 | 2015 |
| Spatiotemporal wavelet compression for visualization of scientific simulation data S Li, S Sane, L Orf, P Mininni, J Clyne, H Childs 2017 ieee international conference on cluster computing (cluster), 216-227, 2017 | 29 | 2017 |
| Lossy scientific data compression with SPERR S Li, P Lindstrom, J Clyne 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2023 | 27 | 2023 |
| Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives S Li, N Marsaglia, V Chen, C Sewell, J Clyne, H Childs Eurographics Symposium on Parallel Graphics and Visualization, 2017 | 26 | 2017 |
| Using neural networks for two dimensional scientific data compression L Hayne, J Clyne, S Li 2021 IEEE International Conference on Big Data (Big Data), 2956-2965, 2021 | 12 | 2021 |
| Performance Impacts of In Situ Wavelet Compression on Scientific Simulations S Li, J Clyne, M Larsen, H Childs ISAV'17 Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale …, 2017 | 12 | 2017 |
| Exploring hierarchical visualization designs using phylogenetic trees S Li, RJ Crouser, G Griffin, C Gramazio, HJ Schulz, H Childs, R Chang Visualization and Data Analysis 2015 9397, 68-81, 2015 | 10 | 2015 |
| Enabling explorative visualization with full temporal resolution via in situ calculation of temporal intervals N Marsaglia, S Li, H Childs International Conference on High Performance Computing, 273-293, 2018 | 6 | 2018 |
| Error-Controlled Lossy Compression Optimized for High Compression Ratios of Scientific Datasets.(2018) X Liang, S Di, D Tao, S Li, S Li, H Guo, Z Chen, F Cappello | 6 | 2018 |
| HashFight: A platform-portable hash table for multi-core and many-core architectures B Lessley, S Li, H Childs IS&T International Symposium on Electronic Imaging 2020, 2020 | 5 | 2020 |
| Dynamic I/O Budget Reallocation For In Situ Wavelet Compression. N Marsaglia, S Li, K Belcher, M Larsen, H Childs Eurographics Symposium on Parallel Graphics and Visualization, 1-5, 2019 | 2 | 2019 |
| In situ wavelet compression on supercomputers for post hoc exploration S Li, J Clyne, H Childs In Situ Visualization for Computational Science, 37-59, 2022 | 1 | 2022 |
| Optimization of DNS code and visualization of entrainment and mixing phenomena at cloud edges B Kumar, M Rehme, N Suresh, N Cherukuru, S Jaroszynski, S Li, ... Parallel Computing 107, 102811, 2021 | 1 | 2021 |
| Evaluating the Efficacy of Wavelet Compression for Turbulent-Flow Data Visualization S Li | 1 | 2015 |
| An analytical approach for the creative design of new visualizations G Griffin, S Li, C Gramazio, R Chang IEEE InfoVis 11, 2011 | 1 | 2011 |
| Engaging community development in an established earth sciences visualization tool: VAPOR3. J Clyne, S Jaroszynski, S Li, S Pearse Geophysical Research Abstracts 21, 2019 | | 2019 |
John ClyneNational Center for Atmospheric ResearchVerified email at ucar.edu
