Kristal N. Varela , Gabriel I. Pagola , Albert M. Lund , Marta B. Ferraro , Anita M. Orendt , Julio C. Facelli
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引用次数: 0
Abstract
In this paper we report the implementation and testing of algorithmic changes that have been implemented in MGAC, a crystal structure prediction system, to make it scalable and amenable to take advantage of such significant distributed resources as the Open Science Grid (OSG). The changes include the adoption of a steady state Genetic Algorithm (GA) and the adoption of a more general definition of the GA genome that eliminates the need of searching individually for each of the 230 possible space groups and the use of the Density Functional Theory with dispersion correction (DFT-D) as implemented in Quantum Espresso (QE) to calculate crystal energies. The performance of this implementation of MGAC, which in the following we label as MGAC-QE-OSG, is demonstrated for two test cases methanol and ethanol. In both cases the MGAC-QE-OSG can find the experimental structures of these compounds.
期刊介绍:
Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory.
The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation.
This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods.
Computational science typically unifies three distinct elements:
• Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous);
• Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems;
• Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).