high performance computing on graphics processing units: hgpu.org

We present a new technique for sorting data into spatial bins or buckets using a graphics processing unit (GPU). Our method takes unsorted point data as input and scatters the points, in sorted order, into a set of bins. This is a key operation in the construction of spatial data structures, which are essential for […]

Octree structures are widely used in graphic applications to accelerate the computation of geometric proximity relations. This data strucutre is fundamental for game engine architectures for a correct scene management and culling process. With the increasing power of graphics hardware, processing tasks are progressively ported of to those architectures. However, octrees are essentially hierarchical structures, […]

The CFD code Overflow includes as one of its solver options a quasi-SSOR algorithm. This is a fairly small piece of code but it accounts for a significant portion of the total computational time. This paper studies some of the issues in accelerating the code by use of a GPU. The algorithm needs to be […]

Visual categorization is important to manage large collections of digital images and video, where textual metadata is often incomplete or simply unavailable. The bag-of-words model has become the most powerful method for visual categorization of images and video. Despite its high accuracy, a severe drawback of this model is its high computational cost. As the […]

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 […]