Posts

Dec, 14

Fast Isosurface Rendering on a GPU by Cell Rasterization

This paper presents a fast, high-quality, GPU-based isosurface rendering pipeline for implicit surfaces defined by a regular volumetric grid. GPUs are designed primarily for use with polygonal primitives, rather than volume primitives, but here we directly treat each volume cell as a single rendering primitive by designing a vertex program and fragment program on a […]
Dec, 14

Fast GPU-based Adaptive Tessellation with CUDA

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 […]
Dec, 14

GPU-based real-time acoustical occlusion modeling

In typical environments, the direct path between a sound source and a listener is often occluded. However, due to the phenomenon of diffraction, sound still reaches the listener by “bending” around an obstacle that lies directly in the line of straight propagation. Modeling occlusion/diffraction effects is a difficult and computationally intensive task and thus generally […]
Dec, 14

Parallel garment drape simulation of triangular mesh using GPU programming

PURPOSE: The purpose of this paper is to determine the possibility of implementing parallel processing feature of graphic processor unit (GPU) in garment drape simulation. DESIGN/METHODOLOGY/APPROACH: Velocity-Verlet method based on explicit integration is used to drape triangular table cloth meshes. Both drape simulation and collision detection engines are converted to GPU version. Simulation speeds of […]
Dec, 14

Real-Time Concurrent Linked List Construction on the GPU

We introduce a method to dynamically construct highly concurrent linked lists on modern graphics processors. Once constructed, these data structures can be used to implement a host of algorithms useful in creating complex rendering effects in real time. We present a straightforward way to create these linked lists using generic atomic operations available in APIs […]
Dec, 14

GPU Rendering of Relief Mapped Conical Frusta

This paper proposes to use relief-mapped conical frusta (cones cut by planes) to skin skeletal objects. Based on this representation, current programmable graphics hardware can perform the rendering with only minimal communication between the CPU and GPU. A consistent definition of conical frusta including texture parametrization and a continuous surface normal is provided. Rendering is […]
Dec, 14

GPU-Assisted High Quality Particle Rendering

Visualizing dynamic participating media in particle form by fully solving equations from the light transport theory is a computationally very expensive process. In this paper, we present a computational pipeline for particle volume rendering that is easily accelerated by the current GPU. To fully harness its massively parallel computing power, we transform input particles into […]
Dec, 14

A Flexible Kernel for Adaptive Mesh Refinement on GPU

We present a flexible GPU kernel for adaptive on-the-fly refinement of meshes with arbitrary topology. By simply reserving a small amount of GPU memory to store a set of adaptive refinement patterns, on-the-fly refinement is performed by the GPU, without any preprocessing nor additional topology data structure. The level of adaptive refinement can be controlled […]
Dec, 14

A GPU based real-time GPS software receiver

Off-the-shelf graphics processing units provide low-cost massive parallel computing performance, which can be utilized for the implementation of a GPS software receiver. In order to realize a real-time capable system the crucial stages of the receiver should be optimized to suit the requirements of a parallel processor. Moreover, the receiver should be capable to provide […]
Dec, 14

Scalable Programming Models for Massively Multicore Processors

Including multiple cores on a single chip has become the dominant mechanism for scaling processor performance. Exponential growth in the number of cores on a single processor is expected to lead in a short time to mainstream computers with hundreds of cores. Scalable implementations of parallel algorithms will be necessary in order to achieve improved […]
Dec, 14

Specular Effects on the GPU: State of the Art

This survey reviews algorithms that can render specular, i.e. mirror reflections, refractions, and caustics on the GPU. We establish a taxonomy of methods based on the three main different ways of representing the scene and computing ray intersections with the aid of the GPU, including ray tracing in the original geometry, ray tracing in the […]
Dec, 14

OpenMP in Multicore Architectures (tech. report)

OpenMP is an API (application program interface) used to explicitly direct multi-threaded, shared memory parallelism. With the advent of Multi-core processors, there has been renewed interest in parallelizing programs. Multi-core offers support to execute threads in parallel but at the same time the cost of communication is very less. This opens up new domains to […]
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Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 11.4
  • SDK: AMD APP SDK 2.8
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 5.0.35, AMD APP SDK 2.8

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

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