The accurate segmentation of liver vessels is an important prerequisite for creating oncologic surgery planning tools as well as medical visualization applications. In this paper, a fully automatic approach is presented to quickly enhance and extract the vascular system of the liver from CT datasets. Our framework consists of three basic modules: vessel enhancement on the graphics processing un...

A three-dimensional (3-D) shape measurement system that can simultaneously achieve 3-D shape acquisition, reconstruction, and display at 30 frames per second (fps) with 480,000 measurement points per frame is presented. The entire processing pipeline was realized on a graphics processing unit (GPU) without the need of substantial central processing unit (CPU) power, making it achievable on a po...

This paper presents the application of graphics processing unit (GPU) based computing to speed-up electromagnetic transient (EMT) simulation of large power systems. In this scheme the GPU is mainly deployed to perform the computationally intensive part of the simulation in parallel using its built-in massively parallel processing cores, and the CPU (conventional central processing unit) is assi...

All room acoustic modeling techniques are computationally demanding due to the underlying complexity of sound propagation. Traditionally, all the modeling methods have been implemented for the central processing unit (CPU) of the computer. Recent trends in terms of programmable many-core processors or graphics processing units (GPU) is resulting in a paradigm shift. Modern GPUs are massively pa...

The increasing array size of radio astronomy interferometers is causing the associated computation to scale quadratically with the number of array signals. Consequently, efficient usage of alternate processing architectures should be explored in order to meet this computational challenge. Affordable parallel processors have been made available to the general scientific community in the form of ...

High Performance Computing (HPC) has recently been considerably improved, for instance General Purpose computation on Graphics Processing Units (GPGPU) has been developed to accelerate parallel computing by using hundreds of cores simultaneously. GPU computing with Compute Unified Device Architecture (CUDA) is a new approach to solve complex problems and transform the GPU into a massively paral...

Modern graphics cards for computers, and especially their graphics processing units (gpus), are designed for fast rendering of graphics. In order to achieve this gpus have a parallel architecture which can be exploited for general-purpose computing on graphics processing units (gpgpu) as a complement to the central processing unit (cpu). In this paper gpgpu techniques are used to implement stat...

Recent advances in the development of large eddy simulation (LES) atmospheric models with corresponding transport and dispersion (AT&D) modeling capabilities have made it possible to simulate short, time-averaged, single realizations pollutant at spatial temporal resolution necessary for common needs, such as designing air sampling networks, assessing sensor system performance, characterizi...

The Graphics Processing Unit (GPU) is gaining popularity as a co-processor to the Central Processing Unit (CPU), due to its ability to surpass the latter’s performance in certain application fields. Nonetheless, harnessing the GPU’s capabilities is a non-trivial exercise that requires good knowledge of parallel programming. Thus, providing ways to extract such computational power has become an ...

We present a novel algorithm to compute the convex hull of a point set in R using the graphics processing unit (GPU). By exploiting the relationship between the Voronoi diagram and the convex hull, we derive the answer from the former. Our algorithm only requires a few simple atomic operations and does not need explicit locking or any other concurrency control mechanism, thus it can maximize th...