high performance computing on graphics processing units: hgpu.org

The Fourier transform is a well known and widely used tool in many scientific and engineering fields. The Fourier transform is essential for many image processing techniques, including filtering, manipulation, correction, and compression. As such, the computer graphics community could benefit greatly from such a tool if it were part of the graphics pipeline. As […]

Abstract  In the field of computer vision, it is becoming increasingly popular to implement algorithms, in sections or in their entirety, on a graphics processing unit (GPU). This is due to the superior speed GPUs offer compared to CPUs. In this paper, we present a GPU library, MinGPU, which contains all of the necessary functions to […]

The kd-tree is a fundamental tool in computer science. Among others, an application of the kd-tree search (oct-tree method) to fast evaluation of particle interactions and neighbor search is highly important since computational complexity of these problems are reduced from O(N^2) with a brute force method to O(N log N) with the tree method where […]

An intrinsic collision detection unit (ICDU) forms the bottom-most layer of a collision detection pipeline. The ICDU performs collision detection and computes collision information for primitive feature pairs of objects in a 3D dynamic environment. A significant amount of time can be spent by the ICDU during the collision detection process. In this paper, we […]

The scan primitives are powerful, general-purpose data-parallel primitives that are building blocks for a broad range of applications. We describe GPU implementations of these primitives, specifically an efficient formulation and implementation of segmented scan , on NVIDIA GPUs using the CUDA API. Using the scan primitives, we show novel GPU implementations of quicksort and sparse […]

In this paper we propose a simple GPU-based approach for discrete incremental approximation of 3D Voronoi diagram. By constructing region maps via GPU. Nearest sites, space clustering, and shortest distance query can be quickly answered by looking up the region map. In addition, we propose another representation of the 3D Voronoi diagram for visualization.

Today Graphics Processing Units (GPUs) are a largely underexploited resource on existing desktops and a possible cost-effective enhancement to high-performance systems. To date, most applications that exploit GPUs are specialized scientific applications. Little attention has been paid to harnessing these highly-parallel devices to support more generic functionality at the operating system or middleware level. This […]

We show how to accelerate the direct solution of the Boltzmann equation using Graphics Processing Units (GPUs). In order to fully exploit the computational power of the GPU, we choose a method of solution which combines a finite difference discretization of the free-streaming term with a Monte Carlo evaluation of the collision integral. The efficiency […]

We use the graphics processing unit (GPU) for fast calculations of helicity amplitudes of physics processes. As our first attempt, we compute $ubaruto nγ$ ($n=2$ to 8) processes in $pp$ collisions at $sqrts = 14$TeV by transferring the MadGraph generated HELAS amplitudes (FORTRAN) into newly developed HEGET ( HELAS Evaluation with GPU Enhanced Technology) codes […]

In this paper, we propose a hardware-accelerated PDE (partial differential equation) solver based on the lattice Boltzmann model (LBM). The LBM is initially designed to solve fluid dynamics by constructing simplified microscopic kinetic models. As an explicit numerical scheme with only local operations, it has the advantage of being easy to implement and especially suitable […]

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 […]