Two block cyclic reduction linear system solvers are considered and implemented using the OpenCL framework. The topics of interest include a simplified scalar cyclic reduction tridiagonal system solver and the impact of increasing the radix-number of the algorithm. Both implementations are tested for the Poisson problem in two and three dimensions, using a Nvidia GTX 580 series GPU and double p...

Evolution through natural selection offers the possibility of automatically generating functionally complex solutions to a wide range of problems. Methods such as Genetic Programming (GP) show the promise of this approach but tend to stagnate after relatively few generations. To research this issue, execution speed must be substantially improved. This thesis presents work to accelerate the exec...

Graphic Processing Units (GPUs) are fast, highly parallel units. In addition to processing 3D graphics, modern GPUs can be programmed for more general-purpose computation. A GPU consists of a large number of ‘shader processors’, and conceptually operates as a single instruction multiple data (SIMD) or multiple instruction multiple data (MIMD) stream processor. A modern GPU can have several hund...

Without doubt, the fast Fourier transform (FFT) belongs to the algorithms with large impact on science and engineering. By appropriate approximations, this scheme has been generalized for arbitrary spatial sampling points. This so called nonequispaced FFT is the core of the sequential NFFT3 library and we discuss its computational costs in detail. On the other hand, programmable graphics proces...

This work investigates the feasibility of implementing an iterative algorithm on a programmable GPU (PGPU) using the Fuzzy C-Means (FCM) algorithm. The PGPU has been shown to provide significant reductions in computation times for a variety of non-iterative algorithms. However the feasibility of implementing complex iterative algorithms within a programmable graphics pipeline has yet to be dete...

The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various algorithms. In this review, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics and quantum simulations for electronic structure calculations using the density functional theory, wave function techniques and quantum...

This paper discusses the potential of graphics processing units (GPUs) in high-dimensional optimization problems. A single GPU card with hundreds of arithmetic cores can be inserted in a personal computer and dramatically accelerates many statistical algorithms. To exploit these devices fully, optimization algorithms should reduce to multiple parallel tasks, each accessing a limited amount of d...