Anton, a special-purpose machine for molecular dynamics simulation

By David E. Shaw, Jack C. Chao, Michael P. Eastwood, Joseph Gagliardo, J. P. Grossman, C. Ho, D. Ierardi, I. Kolossváry, John L. Klepeis, T. Layman and 17 more. 2007

489 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Molecular Biology, Spectroscopy, Optimization & Training

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Citations in the corpus

Chasing Carbon: The Elusive Environmental Footprint of Computing (2020, background): “For salient applications, such as AI [4]–[9], molecular dynamics [10], video encoding [11], and cryptography [12], systems now comprise specialized hardware accelerators that provide orders-of-magnitude higher performance and energy efﬁciency.”
Weighted Ensemble Simulation: Review of Methodology, Applications, and Software (2017, unknown): “Dramatic improvements in achievable computing speed based on hardware advances (44, 56, 60) have transformed the field of biomolecular simulation.”
Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer (2014, methodology): “MD simulations can be accelerated by over an order of magnitude with special-purpose hardware: the firstgeneration Anton machines [45] (referred to here as Anton 1) are capable of simulating multiple microseconds per day for chemical systems in the 10,000- to 500,000-atom range [4, 41].”
Parallel reactive molecular dynamics: Numerical methods and algorithmic techniques (2012, background): “Note that for typical conventional MD codes, the time spent on bonded interactions is significantly lower than that spent on nonbonded interactions [27].”
Protein storytelling through physics (2020, background): “Shaw and colleagues’ special purpose Anton and Anton 2 supercomputer (32, 33).”
Patterns of coevolving amino acids unveil structural and dynamical domains (2017, methodology): “Efforts to clarify the sequence–structure relationship have also followed different routes: from the development of increasingly accurate force fields to be used in unbiased folding simulations (8, 9) to higher-level approaches where structural features are inferred from the sole physicochemical or ”
Computational Methods in Drug Discovery (2014, methodology): “Anton has been used successfully for full atomic resolution protein folding (Lindorff-Larsen et al., 2011).”