4.5k citations · 4.6k across the 10 of their papers we have counts for
3 papers · 1 filter
Towards Electronic Structure-Based Ab-Initio Molecular Dynamics Simulations with Hundreds of Millions of Atoms
Robert Schade, Tobias Kenter, Hossam Elgabarty +8
We push the boundaries of electronic structure-based \textit{ab-initio} molecular dynamics (AIMD) beyond 100 million atoms. This scale is otherwise barely reachable with classical…
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning & HPC Workloads
Evangelos Georganas, Dhiraj Kalamkar, Sasikanth Avancha +16
During the past decade, novel Deep Learning (DL) algorithms, workloads and hardware have been developed to tackle a wide range of problems. Despite the advances in workload and har…
Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case
Florian Rehm, Sofia Vallecorsa, Vikram Saletore +5
Deep learning is finding its way into high energy physics by replacing traditional Monte Carlo simulations. However, deep learning still requires an excessive amount of computation…