105 citations · 505 across the 30 of their papers we have counts for
6 papers · 1 filter
MGARD+: Optimizing Multilevel Methods for Error-bounded Scientific Data Reduction
Xin Liang, Ben Whitney, Jieyang Chen +8
Data management is becoming increasingly important in dealing with the large amounts of data produced by large-scale scientific simulations and instruments. Existing multilevel com…
SDC Resilient Error-bounded Lossy Compressor
Sihuan Li, Sheng Di, Kai Zhao +3
Lossy compression is one of the most important strategies to resolve the big science data issue, however, little work was done to make it resilient against silent data corruptions…
Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures
Jiannan Tian, Cody Rivera, Sheng Di +4
Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that da…
cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data
Jiannan Tian, Sheng Di, Kai Zhao +8
Error-bounded lossy compression is a state-of-the-art data reduction technique for HPC applications because it not only significantly reduces storage overhead but also can retain h…
Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs
Jieyang Chen, Lipeng Wan, Xin Liang +8
Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific…
FT-CNN: Algorithm-Based Fault Tolerance for Convolutional Neural Networks
Kai Zhao, Sheng Di, Sihuan Li +6
Convolutional neural networks (CNNs) are becoming more and more important for solving challenging and critical problems in many fields. CNN inference applications have been deploye…