296 citations · 1k across the 84 of their papers we have counts for
5 papers · 1 filter
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…
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…
FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-point Data
Robert Underwood, Sheng Di, Jon C. Calhoun +1
With ever-increasing volumes of scientific floating-point data being produced by high-performance computing applications, significantly reducing scientific floating-point data size…