296 citations · 582 across the 15 of their papers we have counts for
25 papers
SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates
Baixi Sun, Xiaodong Yu, Chengming Zhang +7
CNN-based surrogates have become prevalent in scientific applications to replace conventional time-consuming physical approaches. Although these surrogates can yield satisfactory r…
TAC: Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations
Daoce Wang, Jesus Pulido, Pascal Grosset +4
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…
SZx: an Ultra-fast Error-bounded Lossy Compressor for Scientific Datasets
Xiaodong Yu, Sheng Di, Kai Zhao +4
Today's scientific high performance computing (HPC) applications or advanced instruments are producing vast volumes of data across a wide range of domains, which introduces a serio…
SIMD Lossy Compression for Scientific Data
Griffin Dube, Jiannan Tian, Sheng Di +3
Modern HPC applications produce increasingly large amounts of data, which limits the performance of current extreme-scale systems. Data reduction techniques, such as lossy compress…
Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights
Bo Fang, Daoce Wang, Sian Jin +6
In recent years, the increasing complexity in scientific simulations and emerging demands for training heavy artificial intelligence models require massive and fast data accesses,…
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…