high performance computing on graphics processing units: hgpu.org

Local invariant features have been widely used as fundamental elements for image matching and object recognition. Although dense sampling of local features is useful in achieving an improved performance in image matching and object recognition, it results in increased computational costs for feature extraction. The purpose of this paper is to develop fast computational techniques […]

The Matrix-Matrix Multiplication is the most important operation in High-Performance Linear Algebra. If your application can cast most of its computation in terms of the level-3 BLAS operations, the application can achieve very high-performance levels. For this reason the Basic Linear Algebra Subprograms(BLAS) tend to heavily optimize this operation. With Graphics Processing Units(GPUs) on the […]

The graphics processing unit (GPU) has evolved from being a fixed-function processor with programmable stages into a programmable processor with many fixed-function components that deliver massive parallelism. By modifying the GPU’s stream processor to support “general-purpose computation” on the GPU (GPGPU), applications that perform massive vector operations can realize many orders-of-magnitude improvement in performance over […]

MOTIVATION: Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in Genome-Wide Association Studies (GWAS). Boolean operation based screening and testing […]

In computational vision, visual tracking remains one of the most challenging problems due to noise, clutter, occlusion, and dynamic scenes. No one technique has yet managed to solve this problem completely, but those that employ control- theoretic filtering techniques have proven to be quite successful. In this work, we extend one such technique by Niethammer […]

This paper describes how the calculation of depth from stereo images was accelerated using a GPU. The Compute Unified Device Architecture (CUDA) from NVIDIA was employed in novel ways to compute depth using BT cost matching and the semi-global matching algorithm. The challenges of mapping a sequential algorithm to a massively parallel thread environment and […]

Accelerating hardware devices represent a novel promise for im- proving the performance for many problem domains but it is not clear for which domains what accelerators are suitable. While there is no room in general-purpose processor design to significantly in- crease the processor frequency, developers are instead resorting to multi-core chips duplicating conventional computing capabilities […]

With the introduction in 2003 of standard GPUs with 32 bit floating point numbers and programmable Vertex and Fragment processors, the processing power of the GPU was made available to non-graphics applications. As the GPU is aimed at computer graphics, the concepts in GPU-programming are based on computer graphics terminology, and the strategies for programming […]

In this paper we introduce a novel parallel and interactive SPH simulation and rendering method on the GPU using CUDA which allows for high quality visualization. The crucial particle neighborhood search is based on Z-indexing and parallel sorting which eliminates GPU memory overhead due to grid or hierarchical data structures. Furthermore, it overcomes limitations imposed […]

GPU shaders seem used mostly for gaming and other forms of entertainment and simulation. But they have less-obvious visualization uses, for the same reasons that interest the gaming community: improved appearance and performance. This column looks at the use of shaders and the OpenGL shading language (GLSL) in two common visualization applications: point clouds and […]

In this chapter we present an implementation of the anisotropic Kuwahara filter. The anisotropic Kuwahara filter is a generalization of the Kuwahara filter that avoids artifacts by adapting shape, scale and orientation of the filter to the local structure of the input. Due to this adaption, directional image features are better preserved and emphasized. This […]

In “A realtime GPU subdivision kernel” (SIGGRAPH 2005), Shiue et al. showed that, in principle, all major features of subdivision algorithms can be realized in the framework of highly parallel stream processing. Shiue et al. tested the approach by implementing Catmull-Clark subdivision, with semi-smooth creases and global boundaries, in programmable graphics hardware, at near realtime […]