Speeding Up Cycle Based Logic Simulation 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...

Fuzzy Logic System Using Graphics Processing Units - A Survey

In this paper, a comprehensive survey on various applications of Fuzzy Logic system has been carried out. GPU (Graphics Processing Units) is used for speed up purpose, otherwise commonly used for graphics applications. However, recent trends show use of GPU in various other general computational applications to run them parallel to reduce overall execution time. In this paper, it is discussed t...

Pricing derivatives on graphics processing units using Monte Carlo simulation

This paper is about using the existing Monte Carlo approach for pricing European and American contracts on a state-of-the-art graphics processing unit (GPU) architecture. First, we adapt on a cluster of GPUs two different suitable paradigms of parallelizing random number generators, which were developed for CPU clusters. Because in financial applications, we request results within seconds of si...

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 ...