high performance computing on graphics processing units: hgpu.org

Real-time simulation of deformable solids is essential for some applications such as biological organ simulations for surgical simulators. In this work, deformable solids are approximated to be linear elastic, and an easy and straight forward numerical technique, the Finite Point Method (FPM), is used to model three dimensional linear elastostatics. Graphics Processing Unit (GPU) is […]

Local search metaheuristics (LSMs) are efficient methods for solving complex problems in science and industry. They allow significantly to reduce the size of the search space to be explored and the search time. Nevertheless, the resolution time remains prohibitive when dealing with large problem instances. Therefore, the use of GPU-based massively parallel computing is a […]

It is important to construct 3D virtual models of man-made fields in which people work and live. Recent mid-range and long-range laser scanners can be used to acquire 3D shapes of cities, buildings, factories, heavy goods, transportation infrastructure, and so on. However, they tend to produce outliers and very noisy points near silhouettes and sharp […]

This report discusses a CUDA program to compare process times on a GPU and a CPU for a range of task size. The hardware compared are the NVIDIA Tesla C870 GPU and the quad-core Intel Xeon E5410 CPU. The operation is to compute the square root of an array. Due to GPU restrictions, the array […]

In radiotherapy, dose calculation is one of the most important and computationally intensive stages needed in a cancer treatment planning. During current clinical cancer treatment, the dose is calculated before the first treatment session and it will continue until the end of the therapy. However, tumours may change during the treatment and it is needed […]

Fluid simulation has been an active research field in computer graphics for the last 30 years. Stam’s stable fluids method, among others, is used for solving equations that govern fluids. This method solves a sparse linear system during the diffusion and move steps, using either relaxation methods (Jacobi, Gauss-Seidel, etc), Conjugate Gradient (and its variants), […]

The increasing power of GPUs can be used to solve systems of linear equations. This has already been shown for different application areas in CAE. In this paper an iterative solver has been ported to the GPU using the NVIDIA CUDA development system. The solver was intergated into the open source CFD system openFOAM. Performance […]

In this paper we present a novel parallel algorithm for computing the convex hull of a set of points in 3D using CUDA programming model. It is based on the QuickHull approach and starts by constructing an initial tetrahedron using four extreme points, discards internal points, and distributes external points to the four faces. It […]

The most popular heterogeneous many-core platform, the CPU+GPU combination, has received relatively little attention in operating systems research. This platform is already widely deployed: GPUs can be found, in some form, in most desktop and laptop PCs. Used for more than just graphics processing, modern GPUs have proved themselves versatile enough to be adapted to […]

Various powerful polyhedral techniques exist to optimize computation intensive programs effectively. Applying these techniques on any non-trivial program is still surprisingly difficult and often not as effective as expected. Most polyhedral tools are limited to a specific programming language. Even for this language, relevant code needs to match specific syntax that rarely appears in existing […]

Among the compute intensive applications, the FDTD (Finite-Difference-Time-Domain) allows to solve time-dependent differential equations. This method is commonly used in electromagnetism to find solutions to Maxwell equations. Although considered as powerful and flexible, the FDTD algorithm has the disadvantage of having a huge numerical dispersion due to nested loops, which are loops inside other loops […]

The concept of shared memory is known to engineers for a long time: a large block of memory shared between processors to allow for synchronization. But what if there where thousands of threads with hundreds of processors accessing a single memory block. This challenge is discussed in this paper. There are APIs used to program […]