Today's scientific simulations are producing vast volumes of data that cannot be stored and
transferred efficiently because of limited storage capacity, parallel I/O bandwidth, and …

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 …

Efficient error-controlled lossy compressors are becoming critical to the success of today's
large-scale scientific applications because of the ever-increasing volume of data produced …

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

Training Graph Neural Networks (GNNs) on large graphs is a fundamental challenge due to
the high memory usage, which is mainly occupied by activations (eg, node embeddings) …

Error-bounded lossy compression is becoming an indispensable technique for the success
of today's scientific projects with vast volumes of data produced during the simulations or …

Error-bounded lossy compression has been identified as a promising solution for
significantly reducing scientific data volumes upon users' requirements on data distortion …

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

Error-bounded lossy compression has been effective in significantly reducing the data
storage/transfer burden while preserving the reconstructed data fidelity very well. Many error …

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