We propose an unsupervised machine-learning checkpoint-restart (CR) algorithm for
particle-in-cell (PIC) algorithms using Gaussian mixtures (GM). The algorithm compresses …

High-performance computing (HPC) systems that run scientific simulations of significance
produce a large amount of data during runtime. Transferring or storing such big datasets …

Lossy compression on scientific data is coming into prominence as the scientific workflow is
hampered significantly by large amounts of data produced by high-performance computing …

Recent years have witnessed a wide adoption of various lossy compression techniques to
alleviate the burden on high-performance computing (HPC) systems that run large-scale …

Modern wind turbines are monitored by sensors that generate massive amounts of time
series data that is ingested on the edge before it is transferred to the cloud where it is stored …

Modern wind turbines are monitored by sensors that generate massive amounts of high
frequency time series that are ingested on the edge and then transferred to the cloud where …

High-performance computing (HPC) applications produce extreme volumes of data that
capture simulation states for failure/restart and post-simulation data analysis. Transferring …