Aidan P. Thompson

发表

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

Christian Trott, Aidan P. Thompson, Laura P. Swiler, 2014, J. Comput. Phys..

A Path to the Exascale for Atomistic Simulations with Improved Accuracy, Length and Time Scales

Anders M. N. Niklasson, Aidan P. Thompson, Danny Perez, 2020 .

Molecular Dynamics Simulation: Engine of Discovery or Bridge to Nowhere?

Aidan P. Thompson, 2019 .

ACCELERATING FINITE-TEMPERATURE KOHN-SHAM DENSITY FUNCTIONAL THEORY pdf

Sivasankaran Rajamanickam, J. Austin Ellis, Aidan P. Thompson, 2020 .

Evaluating the feasibility of using memory content similarity to improve system resilience

Kurt B. Ferreira, Patrick G. Bridges, Scott Levy, 2013, ROSS '13.

Rapid Exploration of Optimization Strategies on Advanced Architectures using TestSNAP and LAMMPS pdf

Stan Moore, Nicholas Lubbers, Jack Deslippe, 2020, ArXiv.

Simple and efficient algorithms for training machine learning potentials to force data

Nicholas Lubbers, Kipton Barros, Aidan P. Thompson, 2020 .

A study of the viability of exploiting memory content similarity to improve resilience to memory errors

Kurt B. Ferreira, Patrick G. Bridges, Scott Levy, 2015, Int. J. High Perform. Comput. Appl..

SNAP: Strong Scaling High Fidelity Molecular Dynamics Simulations on Leadership-Class Computing Platforms

Simon D. Hammond, Christian Trott, Aidan P. Thompson, 2014, ISC.

Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report.

Stan Gerald Moore, Laura Painton Swiler, Christian Robert Trott, 2012 .

Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys

Anh Tran, Tim Wildey, Aidan P. Thompson, 2020, The Journal of chemical physics.

Massively parallel symplectic algorithm for coupled magnetic spin dynamics and molecular dynamics

Aidan P. Thompson, S. J. Plimpton, Julien Tranchida, 2018, J. Comput. Phys..