Abstract The Joint Laboratory on Extreme-Scale Computing (JLESC) was initiated at the
same time lossy compression for scientific data became an important topic for the scientific …

We describe MGARD, a software providing MultiGrid Adaptive Reduction for floating-point
scientific data on structured and unstructured grids. With exceptional data compression …

Compiler optimization plays an increasingly important role to boost the performance of
machine learning models for data processing and management. With increasingly complex …

Today's large-scale scientific applications running on high-performance computing (HPC)
systems generate vast data volumes. Thus, data compression is becoming a critical …

Lossy compression and asynchronous I/O are two of the most effective solutions for reducing
storage overhead and enhancing I/O performance in large-scale high-performance …

Stream processing prevails and SQL query on streams has become one of the most popular
application scenarios. For example, in 2021, the global number of active IoT endpoints …

Today's graphics processing unit (GPU) applications produce vast volumes of data, which
are challenging to store and transfer efficiently. Thus, data compression is becoming a …

Lossy compression is one of the most efficient solutions to reduce storage overhead and
improve I/O performance for HPC applications. However, existing parallel I/O libraries …

Deep learning has been used in various domains, including Web services. Convolutional
neural networks (CNNs), which are deep learning representatives, are among the most …

Numerous applications today rely on artificial intelligence over images. Image AI is,
however, extremely expensive. In particular, the inference cost of image AI dominates the …