73 citations · 250 across the 39 of their papers we have counts for
3 papers · 1 filter
Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations
Attila Cangi, Lenz Fiedler, Bartosz Brzoza +11
We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for…
Breaking the mold: overcoming the time constraints of molecular dynamics on general-purpose hardware
Danny Perez, Aidan Thompson, Stan Moore +11
The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved w…
Breaking the Molecular Dynamics Timescale Barrier Using a Wafer-Scale System
Kylee Santos, Stan Moore, Tomas Oppelstrup +11
Molecular dynamics (MD) simulations have transformed our understanding of the nanoscale, driving breakthroughs in materials science, computational chemistry, and several other fiel…