high performance computing on graphics processing units: hgpu.org

In this paper, we introduce a new real-time rendering algorithm for virtual endoscopy based on GPU. The algorithm reduces the amount of data collected by the Image Memory without affecting 3-D image display accuracy. And it can be applied to compute any complex ray-generation and rendering clips in the volume rendering, making use of GPU’s […]

In the basis of photon texture data generated by parallelized algorithm, we propose the real-time rendering algorithm. This method stores pre-computed results of photon mapping as textures before rendering, and looks for adjacent photons by programming on GPU (graphics processing unit). The algorithm takes full advantage of the computing capacity of GPU to accelerate the […]

GPU shaders aren’t just for special effects. Previously, I looked at some uses for them in visualization. Here, the idea continues. Because visualization relies so much on high speed interaction, we use shaders for the same reason we use them in effects programming: appearance and performance. In the drive to understand large, complex data sets, […]

This paper presents a novel approach to implementing dynamic LOD on GPU. For our purpose, a quadtree structure is created based on seamless geometry image atlas, which is a 3D surface representation in parameter space by combining the features of geometry images and poly-cube maps. All the nodes in the quadtree are packed into the […]

Forward-projection is an important process of computed tomography reconstruction. An accurate forward-projection has a significant impact on increasing the reconstructed quality of iterative algorithms. However its computations are very costly. In order to improve performance of forward-projection, we proposed a GPU-accelerated scheme for it with a new sampling method. There are two novel techniques in […]

We present a fast algorithm for converting quad meshes on the GPU to smooth surfaces. Meshes with 12,000 input quads, of which 60% have one or more non-4-valent vertices, are converted, evaluated and rendered with 9times9 resolution per quad at 50 frames per second. The conversion reproduces bi-cubic splines wherever possible and closely mimics the […]

Real-time video enhancement is generally achieved using costly specialized hardware that have specific functions and outputs. Commercial off-the-shelf hardware, such as desktop computers with Graphics Processing Units (GPUs), are also commonly used as cost effective solutions for real-time video processing. In the past, the limitations in computer hardware meant that real-time video enhancement was mainly […]

In a high performance multiple-input multiple-output (MIMO) system, a soft output MIMO detector combined with a channel decoder is often used at the receiver to maximize performance gain. Graphic processor unit (GPU) is a low-cost parallel programmable co-processor that can deliver extremely high computation throughput and is well suited for signal processing applications. We propose […]

Support Vector Machine (SVM) is one of the most popular tools for solving general classification and regression problems because of its high predicting accuracy. However, the training phase of nonlinear kernel based SVM algorithm is a computationally expensive task, especially for large datasets. In this paper, we propose an intelligent system to solve large classification […]

Quantitative SPECT and PET is not possible without accurate modeling of Compton scatter. The physics of this interaction is well-understood and Monte Carlo and analytical calculations are possible. However, such approaches require exorbitant computing times that limit their practical value in the clinical setting. We present a novel computational model that considerably reduces the computation […]

Adaptively Sampled Distance Fields (ADFs) are volumetric shape representations that support a broad range of applications in the areas of computer graphics, computer vision and physics. ADFs are especially beneficial for representing shapes with features at very diverse scales. In this paper, we propose a strategy to represent and reconstruct ADFs on modern graphics hardware […]

The inherent massive parallelism of cellular neural networks makes them an ideal computational platform for kernel-based algorithms and image processing. General-purpose GPUs provide similar massive parallelism, but it can be difficult to design algorithms to make optimal use of the hardware. The presented research includes a GPU abstraction based on cellular neural networks. The abstraction […]