high performance computing on graphics processing units: hgpu.org

Simulating spiking neural networks is of great interest to scientists wanting to model the functioning of the brain. However, large-scale models are expensive to simulate due to the number and interconnectedness of neurons in the brain. Furthermore, where such simulations are used in an embodied setting, the simulation must be real-time in order to be […]

We present a performance model-driven framework for automated performance tuning (autotuning) of sparse matrix-vector multiply (SpMV) on systems accelerated by graphics processing units (GPU). Our study consists of two parts. First, we describe several carefully hand-tuned SpMV implementations for GPUs, identifying key GPU-specific performance limitations, enhancements, and tuning opportunities. These implementations, which include variants on […]

We present a real-time algorithm to estimate the 3D pose of a previously unseen face from a single range image. Based on a novel shape signature to identify noses in range images, we generate candidates for their positions, and then generate and evaluate many pose hypotheses in parallel using modern graphics processing units (GPUs). We […]

QR decomposition is a computationally intensive linear algebra operation that factors a matrix A into the product of a unitary matrix Q and upper triangular matrix R. Adaptive systems commonly employ QR decomposition to solve overdetermined least squares problems. Performance of QR decomposition is typically the crucial factor limiting problem sizes. Graphics Processing Units (GPUs) […]

Patient-specific biomechanical models implemented using specialized nonlinear (i.e. taking into account material and geometric nonlinearities) finite element procedures were applied to predict the deformation field within the brain for five cases of craniotomy-induced brain shift. The procedures utilize the Total Lagrangian formulation with explicit time stepping. The loading was defined by prescribing deformations on the […]

Computational simulation of time-varying physical processes is of fundamental importance for many scientific and engineering applications. Most frequently, time-varying simulations are performed over multiple spatial grids at discrete points in time. We investigate a new approach to time-varying simulation: spacetime discontinuous Galerkin finite element methods. The result of this simulation method is a simplicial tessellation […]

In this paper, a GPGPU (general purpose graphics processing unit) compatible Archived based Stochastic Ranking Evolutionary Algorithm (G-ASREA) is proposed, that ranks the population with respect to an archive of non-dominated solutions. It reduces the complexity of the deterministic ranking operator from O(mn^2) to O(man)* and further speeds up ranking on GPU. Experiments compare G-ASREA […]

The advent of new matrix-valued magnetic resonance imaging modalities such as Diffusion Tensor Imaging (DTI) requires extensive computational acceleration. Computational acceleration on graphics processing units (GPUs) can make the regularization (denoising) of DTI images attractive in clinical settings, hence improving the quality of DTI images in a broad range of applications. Construction of DTI images […]

Feature detection in flow fields is a well researched area, but practical application is often difficult due to the numerical complexity of the algorithms preventing interactive use and due to noise in experimental or high-resolution simulation data sets. We present an integrated system that provides interactive denoising, vortex detection, and visualization of vector data on […]

We present a system for simulating and visualizing the propagation of dispersive contaminants with an application to urban security. In particular, we simulate airborne contaminant propagation in open environments characterised by sky-scrapers and deep urban canyons. Our approach is based on the multiple relaxation time lattice Boltzmann model (MRTLBM), which can efficiently handle complex boundary […]

Depth enhanced panoramas are a practical solution to the difficult problem of inside-looking-out modeling. Depth enhanced panoramas extend color panoramas to support viewpoint translation, while retaining their speed, convenience, and low cost. Depth enhanced panoramas are built incrementally from same-center-of-projection dense-color and sparse-depth frames that are acquired, registered, and merged at the rate of 5 […]

Proteins are highly flexible and large amplitude deformations of their structure, also called slow dynamics, are often decisive to their function. We present a two-level rendering approach that enables visualization of slow dynamics of large protein assemblies. Our approach is aligned with a hierarchical model of large scale molecules. Instead of constantly updating positions of […]