296 citations · 1k across the 43 of their papers we have counts for
8 papers · 1 filter
Towards Aggregated Asynchronous Checkpointing
Mikaila J. Gossman, Bogdan Nicolae, Jon C. Calhoun +2
High-Performance Computing (HPC) applications need to checkpoint massive amounts of data at scale. Multi-level asynchronous checkpoint runtimes like VELOC (Very Low Overhead Checkp…
Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets
David Krasowska, Julie Bessac, Robert Underwood +3
Lossy compression plays a growing role in scientific simulations where the cost of storing their output data can span terabytes. Using error bounded lossy compression reduces the a…
SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors
Xin Liang, Kai Zhao, Sheng Di +9
Today's scientific simulations require a significant reduction of data volume because of extremely large amounts of data they produce and the limited I/O bandwidth and storage spac…
Improving Prediction-Based Lossy Compression Dramatically via Ratio-Quality Modeling
Sian Jin, Sheng Di, Jiannan Tian +3
Error-bounded lossy compression is one of the most effective techniques for scientific data reduction. However, the traditional trial-and-error approach used to configure lossy com…
Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs
Jiannan Tian, Sheng Di, Xiaodong Yu +7
Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) archit…
Exploring Autoencoder-based Error-bounded Compression for Scientific Data
Jinyang Liu, Sheng Di, Kai Zhao +5
Error-bounded lossy compression is becoming an indispensable technique for the success of today's scientific projects with vast volumes of data produced during simulations or instr…
VELOC: VEry Low Overhead Checkpointing in the Age of Exascale
Bogdan Nicolae, Adam Moody, Gregory Kosinovsky +2
Checkpointing large amounts of related data concurrently to stable storage is a common I/O pattern of many HPC applications. However, such a pattern frequently leads to I/O bottlen…
SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors
Kai Zhao, Sheng Di, Xin Liang +5
Efficient error-controlled lossy compressors are becoming critical to the success of today's large-scale scientific applications because of the ever-increasing volume of data produ…