Acceleration of Generalized Minimum Aberration Designs of Hadamard Matrices on Graphics Processing Units. - Jon Calhoun 001; Josh Graham; Hong Zhou; Hai Jiang 003 (HPCC-ICESS, 2012)

Preemption of a CUDA Kernel Function. - Jon Calhoun 001; Hai Jiang 003 (SNPD, 2012)

FlipIt: An LLVM Based Fault Injector for HPC. - Jon Calhoun 001; Luke N. Olson; Marc Snir (Euro-Par Workshops (1), 2014)

Understanding the Propagation of Error Due to a Silent Data Corruption in a Sparse Matrix Vector Multiply. - Jon Calhoun 001; Marc Snir; Luke N. Olson; María Jesús Garzarán (CLUSTER, 2015)

Towards a more fault resilient multigrid solver. - Jon Calhoun 001; Luke N. Olson; Marc Snir; William D. Gropp (SpringSim (HPS), 2015)

IPAS: intelligent protection against silent output corruption in scientific applications. - Ignacio Laguna; Martin Schulz 001; David F. Richards; Jon Calhoun 001; Luke N. Olson (CGO, 2016)

Towards a More Complete Understanding of SDC Propagation. - Jon Calhoun 001; Marc Snir; Luke N. Olson; William D. Gropp (HPDC, 2017)

From detection to optimization: impact of soft errors on high-performance computing applications - Jon Calhoun 001 (2017)

Energy Analysis and Optimization for Resilient Scalable Linear Systems. - Zheng Miao; Jon Calhoun 001; Rong Ge 002 (CLUSTER, 2018)

Real-time Pedestrian Detection Approach with an Efficient Data Communication Bandwidth Strategy. - Mizanur Rahman; Mhafuzul Islam; Jon C. Calhoun; Mashrur Chowdhury (CoRR, 2018)

Analyzing the Impact of Lossy Compressor Variability on Checkpointing Scientific Simulations. - Pavlo Triantafyllides; Tasmia Reza; Jon C. Calhoun (CLUSTER, 2019)

Towards Data-Driven Approximate Circuit Design. - Ling Qiu; Ziji Zhang; Jon Calhoun 001; Yingjie Lao (ISVLSI, 2019)

FaultSight: A Fault Analysis Tool for HPC Researchers. - Einar Horn; Dakota Fulp; Jon Calhoun 001; Luke N. Olson (FTXS@SC, 2019)

Exploring the feasibility of lossy compression for PDE simulations. - Jon C. Calhoun; Franck Cappello; Luke N. Olson; Marc Snir; William D. Gropp (Int. J. High Perform. Comput. Appl., 2019)

cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data. - Jiannan Tian; Sheng Di; Kai Zhao 008; Cody Rivera; Megan Hickman Fulp; Robert Underwood; Sian Jin; Xin Liang 001; Jon Calhoun 001; Dingwen Tao; Franck Cappello (PACT, 2020)

Combining Spatial and Temporal Properties for Improvements in Data Reduction. - Megan Hickman Fulp; Ayan Biswas; Jon C. Calhoun (IEEE BigData, 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 (IPDPS, 2020)

Dynamic Error-bounded Lossy Compression (EBLC) to Reduce the Bandwidth Requirement for Real-time Vision-based Pedestrian Safety Applications. - Mizanur Rahman; Mhafuzul Islam; Jon C. Calhoun; Mashrur Chowdhury (CoRR, 2020)

TIGRA: A Tightly Integrated Generic RISC-V Accelerator Interface. - Brad Green; Dillon Todd; Jon C. Calhoun; Melissa C. Smith (CLUSTER, 2021)

Understanding Soft Error Sensitivity of Deep Learning Models and Frameworks through Checkpoint Alteration. - Elvis Rojas; Diego Pérez; Jon C. Calhoun; Leonardo Bautista-Gomez; Terry R. Jones; Esteban Meneses (CLUSTER, 2021)

Relaxed Replication for Energy Efficient and Resilient GPU Computing. - Zheng Miao; Jon C. Calhoun; Rong Ge 002 (FTXS@SC, 2021)

ARC: An Automated Approach to Resiliency for Lossy Compressed Data via Error Correcting Codes. - Dakota Fulp; Alexandra Poulos; Robert Underwood; Jon C. Calhoun (HPDC, 2021)

Towards Combining Error-bounded Lossy Compression and Cryptography for Scientific Data. - Ruiwen Shan; Sheng Di; Jon C. Calhoun; Franck Cappello (HPEC, 2021)

Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets. - David Krasowska; Julie Bessac; Robert Underwood; Jon C. Calhoun; Sheng Di; Franck Cappello (DRBSD@SC, 2021)

Productive and Performant Generic Lossy Data Compression with LibPressio. - Robert Underwood; Victoriana Malvoso; Jon C. Calhoun; Sheng Di; Franck Cappello (DRBSD@SC, 2021)

Towards Aggregated Asynchronous Checkpointing. - Mikaila J. Gossman; Bogdan Nicolae; Jon C. Calhoun; Franck Cappello; Melissa C. Smith (CoRR, 2021)

Probabilistic Data-Driven Sampling via Multi-Criteria Importance Analysis. - Ayan Biswas; Soumya Dutta; Earl Lawrence; John Patchett; Jon C. Calhoun; James P. Ahrens (IEEE Trans. Vis. Comput. Graph., 2021)

Lossy Compression to Reduce Latency of Local Image Transfer for Autonomous Off-Road Perception Systems. - Max H. Faykus; Bradley Selee; Jon C. Calhoun; Melissa C. Smith (IEEE Big Data, 2022)

Estimating Potential Error in Sampling Interpolation. - Megan Hickman Fulp; Dakota Fulp; Jon C. Calhoun (IEEE Big Data, 2022)

Exploring Data Corruption Inside SZ. - Ruiwen Shan; Jon C. Calhoun (IEEE Big Data, 2022)

BALA-CPD: BALanced and Asynchronous Distributed Tensor Decomposition. - Zheng Miao; Jiajia Li 001; Jon C. Calhoun; Rong Ge 002 (CLUSTER, 2022)

Exploring Light-weight Cryptography for Efficient and Secure Lossy Data Compression. - Ruiwen Shan; Sheng Di; Jon C. Calhoun; Franck Cappello (CLUSTER, 2022)

Exploring the Impacts of Software Cache Configuration for In-line Compressed Arrays. - Sansriti Ranjan; Dakota Fulp; Jon C. Calhoun (HPEC, 2022)

Modeling Power Consumption of Lossy Compressed I/O for Exascale HPC Systems. - Grant Wilkins; Jon C. Calhoun (IPDPS Workshops, 2022)

Efficient Error-Bounded Lossy Compression for CPU Architectures. - Griffin Dube; Jiannan Tian; Sheng Di; Dingwen Tao; Jon C. Calhoun; Franck Cappello (MASCOTS, 2022)

Stale Data Analysis in Intelligent Transportation Platooning Models. - Cavender Holt; Jon C. Calhoun (UEMCON, 2022)

Exploring Data Reduction Techniques for Additive Manufacturing Analysis. - Coleman Nichols; Megan Hickman Fulp; Nathan DeBardeleben; Jon C. Calhoun (DRBSD@SC, 2022)

SIMD Lossy Compression for Scientific Data. - Griffin Dube; Jiannan Tian; Sheng Di; Dingwen Tao; Jon Calhoun 001; Franck Cappello (CoRR, 2022)

Dynamic error-bounded lossy compression to reduce the bandwidth requirement for real-time vision-based pedestrian safety applications. - Mizanur Rahman; Mhafuzul Islam; Cavender Holt; Jon Calhoun 001; Mashrur Chowdhury (J. Real Time Image Process., 2022)

Posits and the state of numerical representations in the age of exascale and edge computing. - Alexandra Poulos; Sally A. McKee; Jon C. Calhoun (Softw. Pract. Exp., 2022)

Critique of "MemXCT: Memory-Centric X-Ray CT Reconstruction With Massive Parallelization" by SCC Team From Clemson University. - Griffin Dube; Cavender Holt; John Hollowell; Sarah Placke; Sansriti Ranjan; Nikolas Heitzig; Jon Calhoun 001 (IEEE Trans. Parallel Distributed Syst., 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)

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 (CLUSTER, 2023)

Modeling Multi-Threaded Aggregated I/O for Asynchronous Checkpointing on HPC Systems. - Mikaila J. Gossman; Bogdan Nicolae; Jon C. Calhoun (ISPDC, 2023)

Lossy and Lossless Compression for BioFilm Optical Coherence Tomography (OCT). - Max Henry Faykus; Jon Calhoun 001; Melissa C. Smith (SC Workshops, 2023)

Recovering Detectable Uncorrectable Errors via Spatial Data Prediction. - Kristen Guernsey; Sarah Placke; Alexandra Poulos; Jon Calhoun 001 (SC Workshops, 2023)

Evaluating the Resiliency of Posits for Scientific Computing. - Benjamin Schlueter; Jon Calhoun 001; Alexandra Poulos (SC Workshops, 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)

SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors. - Xin Liang 001; Kai Zhao 008; 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, 2023)

Performance Implication of Tensor Irregularity and Optimization for Distributed Tensor Decomposition. - Zheng Miao; Jon C. Calhoun; Rong Ge 002; Jiajia Li 001 (ACM Trans. Parallel Comput., 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., 2023)

Accelerated dynamic data reduction using spatial and temporal properties. - Megan Hickman Fulp; Dakota Fulp; Changfeng Zou; Cooper Sanders; Ayan Biswas; Melissa C. Smith; Jon C. Calhoun (Int. J. High Perform. Comput. Appl., 2023)

Evaluating Lossy and Lossless Compression for DICOM Medical Files. - Yizhe Yang; Carson D. Sisk; Jon C. Calhoun (IEEE Big Data, 2024)

Light-weight Steganography for HPC Lossy Compression. - Ruiwen Shan; Jon C. Calhoun (DCC, 2024)

Analyzing an In-line Compression on the Matrix Matrix Multiplication Kernel. - Steven Platt; Jon C. Calhoun (HPEC, 2024)

FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications. - Grant Wilkins; Sheng Di; Jon C. Calhoun; Zilinghan Li; Kibaek Kim; Robert Underwood; Richard Mortier; Franck Cappello (ICDCS, 2024)

Understanding The Effectiveness of Lossy Compression in Machine Learning Training Sets. - Robert Underwood; Jon C. Calhoun; Sheng Di; Franck Cappello (CoRR, 2024)

A Survey on Error-Bounded Lossy Compression for Scientific Datasets. - Sheng Di; Jinyang Liu 003; Kai Zhao 008; Xin Liang 001; Robert Underwood; Zhaorui Zhang; Milan Shah; Yafan Huang; Jiajun Huang 001; Xiaodong Yu 001; Congrong Ren; Hanqi Guo 001; et al. (CoRR, 2024)

Scalable I/O aggregation for asynchronous multi-level checkpointing. - Mikaila J. Gossman; Bogdan Nicolae; Jon C. Calhoun (Future Gener. Comput. Syst., 2024)

Exploration of LLM Lossless Compression on Scientific Data. - Max H. Faykus; Luanzheng Guo; Rizwan A. Ashraf; Jan Strube 001; Jon C. Calhoun; Nathan R. Tallent (IPDPS (Workshops), 2025)

Sensitivity and Impacts on Parallel Compression of Prediction of Lossy Compression Ratios for Scientific Data. - Alexandra Poulos; Robert Underwood; Jon C. Calhoun; Sheng Di; Franck Cappello (IPDPS, 2025)

To Compress or Not to Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O. - Grant Wilkins; Sheng Di; Jon C. Calhoun; Robert Underwood; Franck Cappello (IPDPS, 2025)

Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing. - Franck Cappello; Mario C. Acosta; Emmanuel Agullo; Hartwig Anzt; Jon Calhoun 001; Sheng Di; Luc Giraud; Thomas Grützmacher; Sian Jin; Kentaro Sano; Kento Sato; Amarjit Singh; et al. (Future Gener. Comput. Syst., 2025)

Towards resilient and energy efficient scalable Krylov solvers. - Zheng Miao; Jon C. Calhoun; Rong Ge 002 (Parallel Comput., 2025)

Precision-Aware Video Compression for Reducing Bandwidth Requirements in Video Communication for Vehicle Detection-Based Applications. - Abyad Enan; Jon C. Calhoun; Mashrur Chowdhury (CoRR, 2025)

A Survey on Error-Bounded Lossy Compression for Scientific Datasets. - Sheng Di; Jinyang Liu 003; Kai Zhao 008; Xin Liang 001; Robert Underwood; Zhaorui Zhang; Milan Shah; Yafan Huang; Jiajun Huang 001; Xiaodong Yu 001; Congrong Ren; Hanqi Guo 001; et al. (ACM Comput. Surv., 2025)