1. Addressing the challenges of standalone multi-core simulations in molecular dynamics
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R.O. Ocaya
Abstract
Computational modelling in material science involves mathematical abstractions of force fields between particles with the aim to postulate, develop and understand materials by simulation. The aggregated pairwise interactions of the material’s particles lead to a deduction of its macroscopic behaviours. For practically meaningful macroscopic scales, a large amount of data are generated, leading to vast execution times. Simulation times of hours, days or weeks for moderately sized problems are not uncommon. The reduction of simulation times, improved result accuracy and the associated software and hardware engineering challenges are the main motivations for many of the ongoing researches in the computational sciences. This contribution is concerned mainly with simulations that can be done on a “standalone” computer based on Message Passing Interfaces (MPI), parallel code running on hardware platforms with wide specifications, such as single/multi- processor, multi-core machines with minimal reconfiguration for upward scaling of computational power. The widely available, documented and standardized MPI library provides this functionality through the MPI_Comm_size (), MPI_Comm_rank () and MPI_Reduce () functions. A survey of the literature shows that relatively little is written with respect to the efficient extraction of the inherent computational power in a cluster. In this work, we discuss the main avenues available to tap into this extra power without compromising computational accuracy. We also present methods to overcome the high inertia encountered in single-node-based computational molecular dynamics. We begin by surveying the current state of the art and discuss what it takes to achieve parallelism, efficiency and enhanced computational accuracy through program threads and message passing interfaces. Several code illustrations are given. The pros and cons of writing raw code as opposed to using heuristic, third-party code are also discussed. The growing trend towards graphical processor units and virtual computing clouds for high-performance computing is also discussed. Finally, we present the comparative results of vacancy formation energy calculations using our own parallelized standalone code called Verlet-Stormer velocity (VSV) operating on 30,000 copper atoms. The code is based on the Sutton-Chen implementation of the Finnis-Sinclair pairwise embedded atom potential. A link to the code is also given.
Abstract
Computational modelling in material science involves mathematical abstractions of force fields between particles with the aim to postulate, develop and understand materials by simulation. The aggregated pairwise interactions of the material’s particles lead to a deduction of its macroscopic behaviours. For practically meaningful macroscopic scales, a large amount of data are generated, leading to vast execution times. Simulation times of hours, days or weeks for moderately sized problems are not uncommon. The reduction of simulation times, improved result accuracy and the associated software and hardware engineering challenges are the main motivations for many of the ongoing researches in the computational sciences. This contribution is concerned mainly with simulations that can be done on a “standalone” computer based on Message Passing Interfaces (MPI), parallel code running on hardware platforms with wide specifications, such as single/multi- processor, multi-core machines with minimal reconfiguration for upward scaling of computational power. The widely available, documented and standardized MPI library provides this functionality through the MPI_Comm_size (), MPI_Comm_rank () and MPI_Reduce () functions. A survey of the literature shows that relatively little is written with respect to the efficient extraction of the inherent computational power in a cluster. In this work, we discuss the main avenues available to tap into this extra power without compromising computational accuracy. We also present methods to overcome the high inertia encountered in single-node-based computational molecular dynamics. We begin by surveying the current state of the art and discuss what it takes to achieve parallelism, efficiency and enhanced computational accuracy through program threads and message passing interfaces. Several code illustrations are given. The pros and cons of writing raw code as opposed to using heuristic, third-party code are also discussed. The growing trend towards graphical processor units and virtual computing clouds for high-performance computing is also discussed. Finally, we present the comparative results of vacancy formation energy calculations using our own parallelized standalone code called Verlet-Stormer velocity (VSV) operating on 30,000 copper atoms. The code is based on the Sutton-Chen implementation of the Finnis-Sinclair pairwise embedded atom potential. A link to the code is also given.
Chapters in this book
- Frontmatter i
- Preface of the Book of Proceedings of the Virtual Conference on Computational Science (VCCS-2016) v
- Contents vii
- List of contributing authors xi
- 1. Addressing the challenges of standalone multi-core simulations in molecular dynamics 1
- 2. Optical and magnetic properties of free-standing silicene, germanene and T-graphene system 23
- 3. Theoretical study of the electronic states of newly detected dications. Case of MgS2+ AND SiN2+ 71
- 4. Analytical Solution of Pantograph Equation with Incommensurate Delay 93
- 5. Computational chemistry applied to vibrational spectroscopy: A tool for characterization of nucleic acid bases and some of their 5-substituted derivatives 117
- 6. Mechanism of nucleophilic substitution reactions of 4-(4’-nitro)phenylnitrobenzofurazan ether with aniline in acetonitrile 153
- 7. Computational methods in preformulation study for pharmaceutical solid dosage forms of therapeutic proteins 163
- 8. Computational Investigation of Cationic, Anionic and Neutral Ag2AuN (N = 1–7) Nanoalloy Clusters 173
- 9. Evacuation simulation using Hybrid Space Discretisation and Application to Large Underground Rail Tunnel Station 191
- 10. DFT study of anthocyanidin and anthocyanin pigments for Dye-Sensitized Solar Cells: Electron injecting from the excited states and adsorption onto TiO2 (anatase) surface 205
- 11. Elemental Two-Dimensional Materials Beyond Graphene 219
- Index 229
Chapters in this book
- Frontmatter i
- Preface of the Book of Proceedings of the Virtual Conference on Computational Science (VCCS-2016) v
- Contents vii
- List of contributing authors xi
- 1. Addressing the challenges of standalone multi-core simulations in molecular dynamics 1
- 2. Optical and magnetic properties of free-standing silicene, germanene and T-graphene system 23
- 3. Theoretical study of the electronic states of newly detected dications. Case of MgS2+ AND SiN2+ 71
- 4. Analytical Solution of Pantograph Equation with Incommensurate Delay 93
- 5. Computational chemistry applied to vibrational spectroscopy: A tool for characterization of nucleic acid bases and some of their 5-substituted derivatives 117
- 6. Mechanism of nucleophilic substitution reactions of 4-(4’-nitro)phenylnitrobenzofurazan ether with aniline in acetonitrile 153
- 7. Computational methods in preformulation study for pharmaceutical solid dosage forms of therapeutic proteins 163
- 8. Computational Investigation of Cationic, Anionic and Neutral Ag2AuN (N = 1–7) Nanoalloy Clusters 173
- 9. Evacuation simulation using Hybrid Space Discretisation and Application to Large Underground Rail Tunnel Station 191
- 10. DFT study of anthocyanidin and anthocyanin pigments for Dye-Sensitized Solar Cells: Electron injecting from the excited states and adsorption onto TiO2 (anatase) surface 205
- 11. Elemental Two-Dimensional Materials Beyond Graphene 219
- Index 229
