Posts
Nov, 6
Maintaining constant frame rates in 3D texture-based volume rendering
3D texture-based volume rendering is a popular way of realizing direct volume visualization on graphics hardware. However, the slice-oriented texture memory layout of many current CPUs may lead to a strongly view-dependent performance, which reduces the fields of application of volume rendering. In this short technical note, we propose a slight modification of texture-based volume […]
Nov, 6
Accelerating Dust Temperature Calculations with Graphics Processing Units
When calculating the infrared spectral energy distributions (SEDs) of galaxies in radiation-transfer models, the calculation of dust grain temperatures is generally the most time-consuming part of the calculation. Because of its highly parallel nature, this calculation is perfectly suited for massively parallel general-purpose Graphics Processing Units (GPUs). This paper presents an implementation of the calculation […]
Nov, 6
Fast scale invariant feature detection and matching on programmable graphics hardware
Ever since the introduction of freely programmable hardware components into modern graphics hardware, graphics processing units (GPUs) have become increasingly popular for general purpose computations. Especially when applied to computer vision algorithms where a Single set of Instructions has to be executed on Multiple Data (SIMD), GPU-based algorithms can provide a major increase in processing […]
Nov, 6
Real-time visualization of large volume datasets on standard PC hardware
In medical area, interactive three-dimensional volume visualization of large volume datasets is a challenging task. One of the major challenges in graphics processing unit (GPU)-based volume rendering algorithms is the limited size of texture memory imposed by current GPU architecture. We attempt to overcome this limitation by rendering only visible parts of large CT datasets. […]
Nov, 6
Efficient simulation of large-scale spiking neural networks using CUDA graphics processors
Neural network simulators that take into account the spiking behavior of neurons are useful for studying brain mechanisms and for engineering applications. Spiking Neural Network (SNN) simulators have been traditionally simulated on large-scale clusters, super-computers, or on dedicated hardware architectures. Alternatively, Graphics Processing Units (GP Us) can provide a low-cost, programmable, and high-performance computing platform […]
Nov, 6
Parallel view-dependent refinement of progressive meshes
We present a scheme for view-dependent level-of-detail control that is implemented entirely on programmable graphics hardware. Our scheme selectively refines and coarsens an arbitrary triangle mesh at the granularity of individual vertices, to create meshes that are highly adapted to dynamic view parameters. Such fine-grain control has previously been demonstrated using sequential CPU algorithms. However, […]
Nov, 6
Magnetohydrodynamics simulations on graphics processing units
Magnetohydrodynamics (MHD) simulations based on the ideal MHD equations have become a powerful tool for modeling phenomena in a wide range of applications including laboratory, astrophysical, and space plasmas. In general, high-resolution methods for solving the ideal MHD equations are computationally expensive and Beowulf clusters or even supercomputers are often used to run the codes […]
Nov, 6
SAPPORO: A way to turn your graphics cards into a GRAPE-6
We present Sapporo, a library for performing high-precision gravitational N-body simulations on NVIDIA Graphical Processing Units (GPUs). Our library mimics the GRAPE-6 library, and N-body codes currently running on GRAPE-6 can switch to Sapporo by a simple relinking of the library. The precision of our library is comparable to that of GRAPE-6, even though internally […]
Nov, 6
Graphics Hardware-Based Level-Set Method for Interactive Segmentation and Visualization
This paper presents an efficient graphics hardware-based method to segment and visualize level-set surfaces as interactive rates. Our method is composed of memory manager, level-set solver, and volume renderer. The memory manager which performs in CPU generates page table, inverse page table and available page stack as well as process the activation and inactivation of […]
Nov, 6
PacketShader: a GPU-accelerated software router
We present PacketShader, a high-performance software router framework for general packet processing with Graphics Processing Unit (GPU) acceleration. PacketShader exploits the massively-parallel processing power of GPU to address the CPU bottleneck in current software routers. Combined with our high-performance packet I/O engine, PacketShader outperforms existing software routers by more than a factor of four, forwarding […]
Nov, 5
An Introduction to GPU Accelerated Surgical Simulation
Modern graphics processing units (GPUs) have recently become fully programmable. Thus a powerful and cost-efficient new computational platform for surgical simulations has emerged. A broad selection of publications has shown that scientific computations obtain a significant speedup if ported from the CPU to the GPU. To take advantage of the GPU however, one must understand […]
Nov, 5
Multi-Level Graph Layout on the GPU
This paper presents a new algorithm for force directed graph layout on the GPU. The algorithm, whose goal is to compute layouts accurately and quickly, has two contributions. The first contribution is proposing a general multi-level scheme, which is based on spectral partitioning. The second contribution is computing the layout on the GPU. Since the […]
