GPU-Acceleration of the Hybrid Fluctuating Hydrodynamics and Molecular Dynamics Simulation
| Autor: | Thomas, Pak, 白托馬 |
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| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 Fluid properties at the molecular scale are often investigated using all-atom simulations, which provide the highest level of detail attainable using classical mechanics. On the other hand, the behavior of fluids at the macroscopic scale is modeled by approximating the fluid as a continuous quantity and tracking its evolution by hydrodynamic equations. At the nanoscale both of these modeling paradigms are necessary. A hybrid model implementing molecular dynamics and hydrodynamics has previously been designed for simulations of nanoscale fluids. It implements a novel coupling scheme that associates a collocating grid with each particle. The mapping of particle to field variables and vice versa is then achieved through interpolation of particle and field grids. However, the coupling algorithm has not yet been adapted for high-performance computing (HPC). In recent years, graphics processing units (GPUs) have emerged as a competitive platform for scientific computations. Originally designed for computer graphics, the GPU architecture is optimized for computationally intensive tasks and high data throughput. These features make them attractive and cost-effective alternatives compared to traditional HPC clusters. Therefore, a GPU–CPU framework was chosen as the HPC platform for the hybrid model. This thesis thus presents the design and implementation of a GPU-accelerated simulation of the hybrid model. The objective was to reformulate the original CPU algorithms to expose massive concurrency, implement them on the GPU and achieve the highest computational speedup possible. A novel GPU algorithm was designed for the coupling scheme that uses shared memory as a staging area to perform fast local interpolations. To maximize computational throughput, a two-stage thread mapping was employed with a minimal amount of additional memory overhead. By drastically increasing the computational efficiency of simulations, the spatial and temporal scales that can be explored using the hybrid model were greatly expanded. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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