scholarly journals Performance Characteristics of Hardware Transactional Memory for Molecular Dynamics Application on BlueGene/Q: Toward Efficient Multithreading Strategies for Large-Scale Scientific Applications

2013 ◽  
Author(s):  
Manaschai Kunaseth ◽  
Rajiv K. Kalia ◽  
Aiichiro Nakano ◽  
Priya Vashishta ◽  
David F. Richards ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Large Scale ◽  
Transactional Memory ◽  
Performance Characteristics ◽  
Scientific Applications ◽  
Hardware Transactional Memory

scholarly journals What Scientific Applications can Benefit from Hardware Transactional Memory?

2012 ◽  
Author(s):  
M Schindewolf ◽  
B Bihari ◽  
J Gyllenhaal ◽  
M Schulz ◽  
A Wang ◽  
...  
Keyword(s):  
Transactional Memory ◽  
Scientific Applications ◽  
Hardware Transactional Memory

Combustion Driven by Fragment-based Ab Initio Molecular Dynamics Simulation

2019 ◽  
Author(s):  
Liqun Cao ◽  
Jinzhe Zeng ◽  
Mingyuan Xu ◽  
Chih-Hao Chin ◽  
Tong Zhu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ab Initio ◽  
Large Scale ◽  
Methane Combustion ◽  
Combustion Method ◽  
Dynamics Simulation ◽  
Ab Initio Molecular Dynamics ◽  
Computational Time ◽  
Combustion Mechanism ◽  
Daily Lives

Combustion is a kind of important reaction that affects people's daily lives and the development of aerospace. Exploring the reaction mechanism contributes to the understanding of combustion and the more efficient use of fuels. Ab initio quantum mechanical (QM) calculation is precise but limited by its computational time for large-scale systems. In order to carry out reactive molecular dynamics (MD) simulation for combustion accurately and quickly, we develop the MFCC-combustion method in this study, which calculates the interaction between atoms using QM method at the level of MN15/6-31G(d). Each molecule in systems is treated as a fragment, and when the distance between any two atoms in different molecules is greater than 3.5 Å, a new fragment involved two molecules is produced in order to consider the two-body interaction. The deviations of MFCC-combustion from full system calculations are within a few kcal/mol, and the result clearly shows that the calculated energies of the different systems using MFCC-combustion are close to converging after the distance thresholds are larger than 3.5 Å for the two-body QM interactions. The methane combustion was studied with the MFCC-combustion method to explore the combustion mechanism of the methane-oxygen system.

Evolution of Metastable Structures in Bimetallic Catalysts from Microscopy and Machine-Learning Molecular Dynamics

2020 ◽  
Author(s):  
Jin Soo Lim ◽  
Jonathan Vandermause ◽  
Matthijs A. van Spronsen ◽  
Albert Musaelian ◽  
Christopher R. O’Connor ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Large Scale ◽  
Materials Science ◽  
Complete Characterization ◽  
Layer By Layer ◽  
Surface Restructuring ◽  
Metastable Structures ◽  
Mechanistic Investigation ◽  
Underlying Mechanisms

Restructuring of interface plays a crucial role in materials science and heterogeneous catalysis. Bimetallic systems, in particular, often adopt very different composition and morphology at surfaces compared to the bulk. For the first time, we reveal a detailed atomistic picture of the long-timescale restructuring of Pd deposited on Ag, using microscopy, spectroscopy, and novel simulation methods. Encapsulation of Pd by Ag always precedes layer-by-layer dissolution of Pd, resulting in significant Ag migration out of the surface and extensive vacancy pits. These metastable structures are of vital catalytic importance, as Ag-encapsulated Pd remains much more accessible to reactants than bulk-dissolved Pd. The underlying mechanisms are uncovered by performing fast and large-scale machine-learning molecular dynamics, followed by our newly developed method for complete characterization of atomic surface restructuring events. Our approach is broadly applicable to other multimetallic systems of interest and enables the previously impractical mechanistic investigation of restructuring dynamics.

Analysing software prefetching opportunities in hardware transactional memory

2021 ◽  
Author(s):  
Marina Shimchenko ◽  
Rubén Titos-Gil ◽  
Ricardo Fernández-Pascual ◽  
Manuel E. Acacio ◽  
Stefanos Kaxiras ◽  
...  
Keyword(s):  
Transactional Memory ◽  
Hardware Transactional Memory ◽  
Software Prefetching
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