Ray-based modeling and imaging in viscoelastic media using graphics processing units

Fuzzy Logic-Based Image Processing Using Graphics Processor Units

This paper introduces a parallelization of fuzzy logicbased image processing using Graphics Processor Units (GPUs). Using an NVIDIA 8800 Ultra, a 126 time speed improvement can be made to fuzzy edge extraction making its processing real-time. The GPU can process approximately 42 frames per second at 640x480 image resolution, thus 307,200 inference processes per frame. With a computational speed...

Fast Density-Based Clustering Using Graphics Processing Units

Data Mining Using Graphics Processing Units

During the last few years, Graphics Processing Units (GPU) have evolved from simple devices for the display signal preparation into powerful coprocessors that do not only support typical computer graphics tasks such as rendering of 3D scenarios but can also be used for general numeric and symbolic computation tasks such as simulation and optimization. As major advantage, GPUs provide extremely ...

Accelerating Genetic Programming Using Graphics Processing Units

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...

Iterative Solutions using Programmable Graphics Processing Units

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...