SPILADY: A Parallel CPU and GPU Code for Spin-Lattice Magnetic Molecular Dynamics Simulations
| Main Author: | Ballantyne, John |
|---|---|
| Other Authors: | Ma, Pui-Wai, Dudarev, S. L., Woo, C. H. |
| Format: | Dataset |
| Terbitan: |
Mendeley
, 2016
|
| Subjects: | |
| Online Access: |
https:/data.mendeley.com/datasets/x3nyy26fp3 |
| ctrlnum |
0.17632-x3nyy26fp3.1 |
|---|---|
| fullrecord |
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<dc><creator>Ballantyne, John</creator><title>SPILADY: A Parallel CPU and GPU Code for Spin-Lattice Magnetic Molecular Dynamics Simulations</title><publisher>Mendeley</publisher><description>Spin–lattice dynamics generalizes molecular dynamics to magnetic materials, where dynamic variables describing an evolving atomic system include not only coordinates and velocities of atoms but also directions and magnitudes of atomic magnetic moments (spins). Spin–lattice dynamics simulates the collective time evolution of spins and atoms, taking into account the effect of non-collinear magnetism on interatomic forces. Applications of the method include atomistic models for defects, dislocations and surfaces in magnetic materials, thermally activated diffusion of defects, magnetic phase transitions, and various magnetic and lattice relaxation phenomena. Spin–lattice dynamics retains all the capabilities of molecular dynamics, adding to them the treatment of non-collinear magnetic degrees of freedom. The spin–lattice dynamics time integration algorithm uses symplectic Suzuki–Trotter decomposition of atomic coordinate, velocity and spin evolution operators, and delivers highly accurate numerical solutions of dynamic evolution equations over extended intervals of time. The code is parallelized in coordinate and spin spaces, and is written in OpenMP C/C++ for CPU and in CUDA C/C++ for Nvidia GPU implementations. Temperatures of atoms and spins are controlled by Langevin thermostats. Conduction electrons are treated by coupling the discrete spin–lattice dynamics equations for atoms and spins to the heat transfer equation for the electrons. Worked examples include simulations of thermalization of ferromagnetic bcc iron, the dynamics of laser pulse demagnetization, and collision cascades.</description><subject>Natural Sciences</subject><contributor>Ma, Pui-Wai</contributor><contributor>Dudarev, S. L.</contributor><contributor>Woo, C. H.</contributor><type>Other:Dataset</type><identifier>10.17632/x3nyy26fp3.1</identifier><rights>Apache License 2.0</rights><rights>http://www.apache.org/licenses/LICENSE-2.0</rights><relation>https:/data.mendeley.com/datasets/x3nyy26fp3</relation><date>2016-09-16T15:25:10Z</date><recordID>0.17632-x3nyy26fp3.1</recordID></dc>
|
| format |
Other:Dataset Other |
| author |
Ballantyne, John |
| author2 |
Ma, Pui-Wai Dudarev, S. L. Woo, C. H. |
| title |
SPILADY: A Parallel CPU and GPU Code for Spin-Lattice Magnetic Molecular Dynamics Simulations |
| publisher |
Mendeley |
| publishDate |
2016 |
| topic |
Natural Sciences |
| url |
https:/data.mendeley.com/datasets/x3nyy26fp3 |
| contents |
Spin–lattice dynamics generalizes molecular dynamics to magnetic materials, where dynamic variables describing an evolving atomic system include not only coordinates and velocities of atoms but also directions and magnitudes of atomic magnetic moments (spins). Spin–lattice dynamics simulates the collective time evolution of spins and atoms, taking into account the effect of non-collinear magnetism on interatomic forces. Applications of the method include atomistic models for defects, dislocations and surfaces in magnetic materials, thermally activated diffusion of defects, magnetic phase transitions, and various magnetic and lattice relaxation phenomena. Spin–lattice dynamics retains all the capabilities of molecular dynamics, adding to them the treatment of non-collinear magnetic degrees of freedom. The spin–lattice dynamics time integration algorithm uses symplectic Suzuki–Trotter decomposition of atomic coordinate, velocity and spin evolution operators, and delivers highly accurate numerical solutions of dynamic evolution equations over extended intervals of time. The code is parallelized in coordinate and spin spaces, and is written in OpenMP C/C++ for CPU and in CUDA C/C++ for Nvidia GPU implementations. Temperatures of atoms and spins are controlled by Langevin thermostats. Conduction electrons are treated by coupling the discrete spin–lattice dynamics equations for atoms and spins to the heat transfer equation for the electrons. Worked examples include simulations of thermalization of ferromagnetic bcc iron, the dynamics of laser pulse demagnetization, and collision cascades. |
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IOS7969.0.17632-x3nyy26fp3.1 |
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Universitas Islam Indragiri |
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onesearch.perpusnas.go.id |
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804 |
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library:university library |
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Teknologi Pangan UNISI |
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2816 |
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Artikel mulono |
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7969 |
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INDRAGIRI HILIR |
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RIAU |
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1 |
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IOS7969 |
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2020-04-08T08:32:31Z |
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dc |
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1686587768209145856 |
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17.204819 |