high performance computing on graphics processing units: hgpu.org

We present an optimized algorithm to compute 3D distance fields using the bilinear interpolation capabilities of GPUs while preserving the features of the model. For a geometric model, our algorithm computes the Euclidean distance fields on each 2D slice of a 3D grid by applying linear decomposition to the non-linear distance function of each primitive […]

Zernike moments are trascendental digital image descriptors used in many application areas like biomedical image processing and computer vision due to their good properties of orthogonality and rotation invariance. However, their computation is too expensive and limits its application in practice, overall when real-time constraints are imposed. This work introduces a novel approach to the […]

We describe a new approach to vision-based 3D object tracking, using appearance-based particle filters to follow 3D model reconstructions. This method is targeted towards modern graphics processors, which are optimized for 3D reconstruction and are capable of highly parallel computation. We discuss an OpenGL implementation of this approach, which uses two rendering passes to update […]

Creating and rendering realistic ocean is one of the most daunting tasks in computer graphics. An efficient algorithm is used to render ocean waves by taking advantage of the parallelism and programmability of GPU and the new characteristics of vertex sampling of Shader Model 3.0. The ocean modeling is optimized by level-of-detail (LOD) technology. The […]

We describe an experimental system for parallel distributed processing of numerical algorithms. Computations are performed on GPUs, and communication is facilitated using FPGA-adapters and self-developed interconnects. As case study we have implemented a conjugate gradient solver for the Poisson problem in three dimensions. The work focuses on machine architecture and distributed processing with special emphasis […]

Computational methods for automatic target recognition are constrained by the need to analyze increasingly high-dimensional sensor data in real time. Parallel processing has the potential to speed up computational bottlenecks in many automatic target recognition (ATR) methods. We will implement parallelized versions of target tracking methods and discuss gains in algorithm completion time.

Raytracing dynamic scenes at interactive rates has received a lot of attention recently. We present a few strategies for high performance ray tracing on a commodity GPU. The construction of grids needs sorting, which is fast on GPUs. The grid is thus the acceleration structure of choice for dynamic scenes as per-frame rebuilding is required. […]

The paper describes a set of strategies for mapping irregular codes onto commodity graphics hardware. We start identifying the resources that current GPUs contain for solving indirect array accesses entirely on hardware, like vertices, textures and color tables. We then show how multiple indirections can be mapped onto the graphics pipeline, basically taking advantage of […]

It is a well-known fact that genetic algorithms (GAs) are ideal for parallel computers due to their ability to parallely evaluate population members. Most past parallel GA studies have exploited this aspect. Besides resorting to completely different algorithms, such as island models etc., a GA involves a number of other operations which, if parallelized properly, […]

Genetic Algorithms(GAs) are suitable for parallel computing since population members fitness maybe evaluated in parallel. Most past parallel GA studies have exploited this aspect, besides resorting to different algorithms, such as island, single-population master-slave, fine-grained and hybrid models. A GA involves a number of other operations which, if parallelized, may lead to better parallel GA […]

This paper addresses the problem of camera tracking and 3D reconstruction from image sequences, i.e., the monocular SLAM problem. Traditionally, this problem is solved using non-linear minimization techniques that are very accurate but hardly used in real time. This work presents a highly parallelizable random sampling approach based on Monte Carlo simulations that fits very […]

Pulsed Wave (PW) spectrum Doppler ultrasound is a valuable tool for clinical diagnosis for flow velocity distribution in vessels. However, real-time processing of PW spectrum is computationally intensive, involving wall filtering, Fast Fourier Transform (FFT), column filtering and linear averaging. In this paper a very efficient implementation of a PW Doppler spectrum ultrasound using the […]