High Performance Computing using GPGPU's

Computer based simulation software having a basis in numerical methods play a major role in research in the area of natural and physical sciences. These tools allow scientists to attempt problems that are too large to solve using analytical methods. But even these tools can fail to give solutions due to computational or storage limits. However, as the performance of computer hardware gets better and better, the computational limits can be also addressed. One such area of work is that of magnetic field modeling, which plays a crucial role in various fields of research, especially those related to nanotechnology. Due to remarkable advancements made in this field, magnetic modelling has developed new found interest, and rightly so. The most significant impact of this interest is perhaps felt in increasing areal densities for data storage devices which is projected to reach almost atomic scales. Computational limits, and subsequently their solutions based on hardware delivering high performance, are therefore a key component in research in this field. The scale of length and time plays a crucial role in observing magnetic phenomena, and as these scales are reduced, new behaviours can be observed. Coarser scales may be beneficial if modeling larger systems, but when working with sub-μm scales, a finer scale has to be selected. Doing so will project the proper magnetic behaviour of the materials, but will come with its share of problems. These will be addressed in this thesis. Simulations are usually configured before being started. The configuration is performed using scripting based methods which need to reflect the proper environmental conditions. For example, simulating multiple bodies with varying orientations, non-uniform geometries, bodies consisting of multiple layers with each layer having different properties, etc. will all need different configuration methods. A performance based solution would need to be optimized for each type of simulation. This may require re-structuring of different components of a simulator. This thesis is devoted to addressing such problems listed above with a focus on performance based solutions. The scope of the work has been limited to magnetostatic field calculations in particular because they consume the most time in the overall simulation. The scope has also been confined to regular structured rectangular meshes which are popular in major micromagnetic simulation software. Using regular meshes, magnetostatic field calculations can exploit a performance boost by using Fast Fourier Transforms. Therefore, fast FFT libraries using open standards will also be addressed in this thesis. In particular, this thesis will be based on the development process of open standards for magnetic field modeling. The major contribution in this regard includes an OpenCL specific FFT library for GPU’s and a GPU based magnetostatic field solver which is used as an extension to the OOMMF simulator. The thesis covers some novel numerical techniques that have been developed to target particular simulation configurations to obtain maximum performance