Modern scientific applications and supercomputing systems are generating large amounts of
data in various fields, leading to critical challenges in data storage footprints and …

With the development of loT and edge computing, data analytics on edge has become
popular, and text analytics directly on compression (TADOC) has been proven to be a …

Due to the increasing scale of high-performance computing (HPC) systems, transient
hardware faults have become a major reliability concern. Consequently, Silent Data …

Regression models are employed in lossless compression of time series data, by storing the
residual of each point, known as regression encoding. Owing to value fluctuation, the …

Error-bounded lossy compression turns more and more important for the data-moving
intensive applications to deal with big datasets efficiently in HPC environments, which often …

Modern HPC applications produce extremely large amounts of scientific data, which cannot
be stored and transferred efficiently. Error-bounded lossy compression has been effective in …