Fast GPU-based Adaptive Tessellation with CUDA
نویسندگان
چکیده
Compact surface descriptions like higher-order surfaces are popular representations for both modeling and animation. However, for fast graphics-hardware-assisted rendering, they usually need to be converted to triangle meshes. In this paper, we introduce a new framework for performing on-the-fly crack-free adaptive tessellation of surface primitives completely on the GPU. Utilizing CUDA and its flexible memory write capabilities, we parallelize the tessellation task at the level of single surface primitives. We are hence able to derive tessellation factors, perform surface evaluation as well as generate the tessellation topology in real-time even for large collections of primitives. We demonstrate the power of our framework by exemplarily applying it to both bicubic rational Bézier patches and PN triangles.
منابع مشابه
Parallelization of Rich Models for Steganalysis of Digital Images using a CUDA-based Approach
There are several different methods to make an efficient strategy for steganalysis of digital images. A very powerful method in this area is rich model consisting of a large number of diverse sub-models in both spatial and transform domain that should be utilized. However, the extraction of a various types of features from an image is so time consuming in some steps, especially for training pha...
متن کاملParallel Implementation of Particle Swarm Optimization Variants Using Graphics Processing Unit Platform
There are different variants of Particle Swarm Optimization (PSO) algorithm such as Adaptive Particle Swarm Optimization (APSO) and Particle Swarm Optimization with an Aging Leader and Challengers (ALC-PSO). These algorithms improve the performance of PSO in terms of finding the best solution and accelerating the convergence speed. However, these algorithms are computationally intensive. The go...
متن کاملFast Histograms using Adaptive CUDA Streams
Histograms are widely used in medical imaging, network intrusion detection, packet analysis and other streambased high throughput applications. However, while porting such software stacks to the GPU, the computation of the histogram is a typical bottleneck primarily due to the large impact on kernel speed by atomic operations. In this work, we propose a stream-based model implemented in CUDA, u...
متن کاملAccelerating high-order WENO schemes using two heterogeneous GPUs
A double-GPU code is developed to accelerate WENO schemes. The test problem is a compressible viscous flow. The convective terms are discretized using third- to ninth-order WENO schemes and the viscous terms are discretized by the standard fourth-order central scheme. The code written in CUDA programming language is developed by modifying a single-GPU code. The OpenMP library is used for parall...
متن کاملGPU Acceleration for Particle Filter based LDPC Decoding
A parallel belief propagation algorithm based on Particle Filtering (PF) for channel estimation and Low-Density Parity-Check (LDPC) decoding is presented in this paper based on Compute Unified Device Architecture (CUDA). The authors have found that compared with the traditional Belief Propagation (BP) algorithm with fixed estimated noise power, BP algorithm based on PF [1] not only gives a good...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Comput. Graph. Forum
دوره 28 شماره
صفحات -
تاریخ انتشار 2009