high performance computing on graphics processing units: hgpu.org

Global optimisation via s-t graph cuts is widely used in computer vision and graphics. To obtain high-resolution output, graph cut methods must construct massive N-D grid-graphs containing billions of vertices. We show that when these graphs do not fit into physical memory, current max-flow/min-cut algorithms-the workhorse of graph cut methods-are totally impractical. Others have resorted […]

Graphics processing units (GPUs), present in every laptop and desktop computer, are potentially powerful computational engines for solving numerical problems. We present a CPU-GPU algorithm for solving linear programming problems using interior point methods. This algorithm, based on the rectangular-packed matrix storage scheme of Gunnels and Gustavson, uses the GPU for computationally intensive tasks such […]

The coding efficiency of the H.264/AVC standard makes the decoding process computationally demanding. This has limited the availability of cost-effective, high-performance solutions. Modern computers are typically equipped with powerful yet cost-effective Graphics Processing Units (GPUs) to accelerate graphics operations. These GPUs can be addressed by means of a 3-D graphics API such as Microsoft Direct3D […]

The recent improvements of graphics processing units (GPU) offer to the computer vision community a powerful processing platform. Indeed, a lot of highly-parallelizable computer vision problems can be significantly accelerated using GPU architecture. Among these algorithms, the k nearest neighbor search (KNN) is a well-known problem linked with many applications such as classification, estimation of […]

In bioinformatics, alignments are commonly performed in genome and protein sequence analysis for gene identification and evolutionary similarities. There are several approaches for such analysis, each varying in accuracy and computational complexity. Smith-Waterman (SW) is by far the best algorithm for its accuracy in similarity scoring. However, execution time of this algorithm on general purpose […]

Taking advantage of the parallelism and programmability of GPU, we solve the fluid dynamics problem completely on GPU. Different from previous methods, the whole computation is accelerated in our method by packing the scalar and vector variables into four channels of texels. In order to be adaptive to the arbitrary boundary conditions, we group the […]

In this article, we describe GPU-Quicksort, an efficient Quicksort algorithm suitable for highly parallel multicore graphics processors. Quicksort has previously been considered an inefficient sorting solution for graphics processors, but we show that in CUDA, NVIDIA’s programing platform for general-purpose computations on graphical processors, GPU-Quicksort performs better than the fastest-known sorting implementations for graphics processors, […]

In the past few years the graphics programmable processor (GPU) has evolved into an increasingly convincing computational resource for non graphics applications. The GPU is especially well suited to address problem sets expressed as data parallel computation with the same program executed on many data elements concurrently. In pursuing a scalable navigation planning approach for […]

We present and analyze different implementations of mass-spring systems for interactive simulation of deformable surfaces on graphics processing units (GPUs). For the amount of springs we target, numerical time integration of spring displacements needs to be accelerated and the transfer of displaced point positions for rendering must be avoided. To fulfill these requirements, we exploit […]

This paper presents an algorithm for fast sorting of large lists using modern GPUs. The method achieves high speed by efficiently utilizing the parallelism of the GPU throughout the whole algorithm. Initially, GPU -based bucketsort or quicksort splits the list into enough sublists then to be sorted in parallel using merge-sort. The algorithm is of […]

This paper presents a study of performance in spatial interaction force simulation. Both CPU-based and GPU-based simulations are examined using a realistic scalable data set. Performance is analyzed for various stages of execution and simulation/optimization parameters.

The emergence of programmable graphics processing units (GPU) has led to increasing interest in off-loading numerically intensive computations on to graphics hardware. DCT/IDCT is widely adopted in modern image/video compression standards and is usually one of the most computationally expensive parts. We present several techniques for efficient implementation of DCT/IDCT on generic programmable GPU, using […]