Robert Underwood
Robert Underwood
Post-Doctoral Apointee, Argonne National Laboratory
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
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
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
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
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
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
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
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
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 …, 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
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
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
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
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
Improving lossy compression for climate datasets with SZ3
F Cappello, S Di, R Underwood
EGU General Assembly Conference Abstracts, EGU22-9741, 2022
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
LibPressio-Predict: Flexible and Fast Infrastructure For Inferring Compression Performance
RR Underwood, S Di, S Jin, MH Rahman, A Khan, F Cappello
Proceedings of the SC'23 Workshops of The International Conference on High …, 2023
A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression
A Ganguli, R Underwood, J Bessac, D Krasowska, JC Calhoun, S Di, ...
2023 IEEE International Conference on Cluster Computing (CLUSTER), 247-258, 2023
Understanding Patterns of Deep Learning ModelEvolution in Network Architecture Search
R Underwood, M Madhastha, R Burns, B Nicolae
arXiv preprint arXiv:2309.12576, 2023
MPIGDB: A Flexible Debugging Infrastructure for MPI Programs
R Underwood, B Nicolae
Proceedings of the 13th Workshop on AI and Scientific Computing at Scale …, 2023
Discussion on “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach”
J Bessac, R Underwood, S Di
Journal of Agricultural, Biological and Environmental Statistics 28 (2), 358-364, 2023
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