high performance computing on graphics processing units: hgpu.org

In the transversal plane CT exhibits a nearly rotational symmetric point spread function. Pixel sampling is typically done on Cartesian grids which are not ideal from a signal processing point of view. It is advantageous to use a hexagonal grid which can capture the same signal components with 13% fewer sampling points. In 3D one […]

In this article we describe stress nets, a technique for exploring 2D tensor fields. Our method allows a user to examine simultaneously the tensors’ eigenvectors (both major and minor) as well as scalar-valued tensor invariants. By avoiding noise-advection techniques, we are able to display both principal directions of the tensor field as well as the […]

We present a physically-based, yet fast and simple method to simulate gaseous phenomena. In our approach, the incompressible Navier-Stokes (NS) equations governing fluid motion have been modeled in a novel way to achieve a realistic animation. We introduce the lattice Boltzmann model (LBM), which simulates the microscopic movement of fluid particles by linear and local […]

This paper presents a signed distance transform algorithm using graphics hardware, which computes the scalar valued function of the Euclidean distance to a given manifold of co-dimension one. If the manifold is closed and orientable, the distance has a negative sign on one side of the manifold and a positive sign on the other. Triangle […]

A comparatively simple approach to highly parallel simulation of Petri nets on commodity, desktop PC hardware is suggested. A mapping, described in the programming language Cg, of Petri net semantics to the SIMD architecture of NVidia 5-series and 6-series GPUs is provided, and a prototype simulator is tested on both conflict-intensive and conflict-free Petri net […]

Stencil computation sweeps over a spatial grid over multiple time steps to perform nearest-neighbor computations. The bandwidth-to-compute requirement for a large class of stencil kernels is very high, and their performance is bound by the available memory bandwidth. Since memory bandwidth grows slower than compute, the performance of stencil kernels will not scale with increasing […]

Geometric Algebra (GA), a generalization of quaternions, is a very powerful form for intuitively expressing and manipulating complex geometric relationships common to engineering problems. The actual evaluation of GA expressions, though, is extremely compute intensive due to the high-dimensionality of data being processed. On standard desktop CPUs, GA evaluations take considerably longer than conventional mathematical […]

Asymptotic and statistical models have been the only practical means, in terms of cost, performance and accuracy, for simulating electrically large environments. We show, in practice, how the combination of commodity graphics processing units (GPUs), and higher-order scaling function based multi-resolution time-domain (S-MRTD) techniques realize an unprecedented high-fidelity full-wave simulator that is orders of magnitude […]

Current GPUs offer specialized graphics hardware in addition to generic floating-point processing units. We propose a method which reuses specialized texture filtering units to perform piecewise polynomial evaluations, which helps accelerate LNS computations and can be used in combination with hardware-based transcendental functions.

Monte-Carlo (MC) simulation is an effective tool for solving complex problems such as many-body simulation, exotic option pricing and partial differential equation solving. The huge amount of computation in MC makes it a good candidate for acceleration using hardware and distributed computing platforms. We propose a novel MC simulation framework suitable for a wide range […]

Sparse matrices are involved in linear systems, eigensystems and partial differential equations from a wide spectrum of scientific and engineering disciplines. Hence, sparse matrix vector product (SpMV) is considered as key operation in engineering and scientific computing. For these applications the optimization of the sparse matrix vector product (SpMV) is very relevant. However, the irregular […]

Graphic Processing Units (GPUs) have evolved to provide a massive computational power. In contrast to Central Processing Units, GPUs are so-called many-core processors with hundreds of cores capable of running thousands of threads in parallel. This parallel processing power can accelerate the simulation of communication systems. In this work, we utilize NVIDIA’s Compute Unified Device […]