Robert Underwood

According to our database, Robert Underwood authored at least 22 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Understanding The Effectiveness of Lossy Compression in Machine Learning Training Sets.

Robert Underwood, Jon C. Calhoun, Sheng Di, Franck Cappello

CoRR, 2024

2023

Black-box statistical prediction of lossy compression ratios for scientific data.

Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello

Int. J. High Perform. Comput. Appl., July, 2023

SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors.

Xin Liang, Kai Zhao, Sheng Di, Sihuan Li, Robert Underwood, Ali Murat Gok, Jiannan Tian, Junjing Deng, Jon C. Calhoun, Dingwen Tao, Zizhong Chen, Franck Cappello

IEEE Trans. Big Data, April, 2023

Efficient Communication in Federated Learning Using Floating-Point Lossy Compression.

Grant Wilkins, Sheng Di, Jon C. Calhoun, Kibaek Kim, Robert Underwood, Richard Mortier, Franck Cappello

CoRR, 2023

Understanding Patterns of Deep Learning ModelEvolution in Network Architecture Search.

Robert Underwood, Meghana Madhyastha, Randal C. Burns, Bogdan Nicolae

CoRR, 2023

The Modern History of ICT in Oceania - PEACESAT and USPNet.

Rieko Hayakawa, Robert Underwood, Jennifer Anson

IEEE Ann. Hist. Comput., 2023

LibPressio-Predict: Flexible and Fast Infrastructure For Inferring Compression Performance.

Robert Underwood, Sheng Di, Sian Jin, Md Hasanur Rahman, Arham Khan, Franck Cappello

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

DStore: A Lightweight Scalable Learning Model Repository with Fine-Grain Tensor-Level Access.

Meghana Madhyastha, Robert Underwood, Randal C. Burns, Bogdan Nicolae

Proceedings of the 37th International Conference on Supercomputing, 2023

A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets.

Md Hasanur Rahman, Sheng Di, Kai Zhao, Robert Underwood, Guanpeng Li, Franck Cappello

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Understanding Patterns of Deep Learning Model Evolution in Network Architecture Search.

Robert Underwood, Meghana Madhyastha, Randal C. Burns, Bogdan Nicolae

Proceedings of the 30th IEEE International Conference on High Performance Computing, 2023

MPIGDB: A Flexible Debugging Infrastructure for MPI Programs.

Robert Underwood, Bogdan Nicolae

Proceedings of the 13th Workshop on AI and Scientific Computing at Scale using Flexible Computing, 2023

A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression.

Arkaprabha Ganguli, Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello

Proceedings of the IEEE International Conference on Cluster Computing, 2023

2022

OptZConfig: Efficient Parallel Optimization of Lossy Compression Configuration.

Robert Underwood, Jon C. Calhoun, Sheng Di, Amy W. Apon, Franck Cappello

IEEE Trans. Parallel Distributed Syst., 2022

ROIBIN-SZ: Fast and Science-Preserving Compression for Serial Crystallography.

Robert Underwood, Chun Hong Yoon, Ali Murat Gok, Sheng Di, Franck Cappello

CoRR, 2022

Understanding the Effects of Modern Compressors on the Community Earth Science Model.

Robert Underwood, Julie Bessac, Sheng Di, Franck Cappello

Proceedings of the 8th IEEE/ACM International Workshop on Data Analysis and Reduction for Big Scientific Data, 2022

2021

Productive and Performant Generic Lossy Data Compression with LibPressio.

Robert Underwood, Victoriana Malvoso, Jon C. Calhoun, Sheng Di, Franck Cappello

Proceedings of the 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data, 2021

Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets.

David Krasowska, Julie Bessac, Robert Underwood, Jon C. Calhoun, Sheng Di, Franck Cappello

Proceedings of the 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data, 2021

ARC: An Automated Approach to Resiliency for Lossy Compressed Data via Error Correcting Codes.

Dakota Fulp, Alexandra Poulos, Robert Underwood, Jon C. Calhoun

Proceedings of the HPDC '21: The 30th International Symposium on High-Performance Parallel and Distributed Computing, 2021

2020

FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-point Data.

Robert Underwood, Sheng Di, Jon C. Calhoun, Franck Cappello

Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data.

Jiannan Tian, Sheng Di, Kai Zhao, Cody Rivera, Megan Hickman Fulp, Robert Underwood, Sian Jin, Xin Liang, Jon Calhoun, Dingwen Tao, Franck Cappello

Proceedings of the PACT '20: International Conference on Parallel Architectures and Compilation Techniques, 2020

2018

Measuring Network Latency Variation Impacts to High Performance Computing Application Performance.

Robert Underwood, Jason Anderson, Amy W. Apon

Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering, 2018

1998

A mathematical programming viewpoint for solving the ultimate pit problem.

Robert Underwood, Boleslaw Tolwinski

Eur. J. Oper. Res., 1998