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 Computer-Aided Design (CAD) applications are used in manufacturing to model
everything from coffee mugs to sports cars. These programs are complex and require years …

Applications in diverse domains such as astronomy, economics and industrial monitoring,
increasingly press the need for analyzing massive collections of time series data. The sheer …

The past decades have witnessed the rapid development of image and video coding
techniques in the era of big data. However, the signal fidelity-driven coding pipeline design …

Networking is crucial for smart city projects nowadays, as it offers an environment where
people and things are connected. This paper presents a chronology of factors on the …

The prevalence of big data has caused a notable surge in both the diversity and magnitude
of data. Consequently, this has prompted the emergence and advancement of two distinct …

Molecular dynamics (MD) has been widely used in today's scientific research across
multiple domains including materials science, biochemistry, biophysics, and structural …

Lempel–Ziv (LZ77) compression is the most commonly used lossless compression
algorithm. The basic idea is to greedily break the input string into blocks (called “phrases”) …

The infrastructure necessary for training state-of-the-art models is becoming overly
expensive, which makes training such models affordable only to large corporations and …

In Implicit Neural Representations (INRs) a discrete signal is parameterized by a neural
network that maps coordinates to the signal samples. INRs were successfully employed for …