AI integration is revolutionizing the landscape of HPC simulations, enhancing the
importance, use, and performance of AI-driven HPC workflows. This paper surveys the …

With the rapid development of technologies such as computer science, big data, and
artificial intelligence, the emergence of a vast amount of data has brought developmental …

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s.
Online analysis methods are needed to enable the collection of only interesting subsets of …

Coherent imaging techniques provide an unparalleled multi-scale view of materials across
scientific and technological fields, from structural materials to quantum devices, from …

A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable)
principles for scientific data is transforming the state-of-practice for data management and …

This study develops a neural network-based approach for emulating high-resolution
modeled precipitation data with comparable statistical properties but at greatly reduced …

Understanding and interpreting dynamics of functional materials in situ is a grand challenge
in physics and materials science due to the difficulty of experimentally probing materials at …

funcX is a distributed function as a service (FaaS) platform that enables flexible, scalable,
and high performance remote function execution. Unlike centralized FaaS systems, funcX …

Scientific applications are increasingly adopting Artificial Intelligence (AI) techniques to
advance science. High-performance computing centers are evaluating emerging novel …

Extremely high data rates at modern synchrotron and X-ray free-electron laser light source
beamlines motivate the use of machine learning methods for data reduction, feature …