high performance computing on graphics processing units: hgpu.org

Today graphics processing units (GPUs) are not only able to generate graphical imaging but also able to expose its multicore architecture to increase computationally heavy general purpose algorithms that can be adapted to the multicore architecture of the GPU. The study conducted in this thesis explores the efficiency of using the general purpose graphics processing […]

An important part of today’s search for hydrocarbon reservoirs such as oil and gas is the use of seismic methods which measure changes in acoustic impedance to explore the interior of the earth. Similar to medical imaging techniques such as MRI or CT, seismic methods generate image slices (survey lines) through the subsurface geology. By […]

In 1980’s time, people believed that computer would help to create more faster and efficient processors. But parallel processing challenged the idea. It joined two or more computers together to solve a problem jointly. It was a trend in 1990 to move away from expansive super computers towards network computers like PCs or Workstations. It […]

We present an approach to molecular-dynamics simulations of dilute ferrofluids on graphics processing units (GPUs). Our numerical scheme is based on a GPU-oriented modification of the Barnes-Hut (BH) algorithm designed to increase the parallelism of computations. For an ensemble consisting of one million of ferromagnetic particles, the performance of the proposed algorithm on a Tesla […]

Direct Volume Rendering of Finite Element models is challenging since the visualisation process is performed in world coordinates, whereas data fields are usually defined over the elements’ material coordinate system. In this paper we present a framework for Direct Volume Rendering of Finite Element models. We present several novel implementations visualising Finite Element data directly […]

Graphics Processing Units (GPUs) have been recently used as coprocessors capable of performing tasks that are not necessarily related to graphics processing in order to optimize computing resources. The use of GPUs has being extended to a wide variety of intensive-computation applications among which audio processing is included. However data transactions between the CPU and […]

This document explains some common methods of visualizing complex functions and how to implement them on the GPU. Using the fragment shader, we visualize complex functions in the complex plane with the domain coloring method. Then using the vertex shader, we visualize complex functions defined on a unit sphere like spherical harmonics. Finally, we redesign […]

GPU-based clusters are an attractive option for parallel volume rendering. One of the key issues in parallel volume rendering is load balancing, keeping a balanced workload per node is essential for improving performance. A good number of dynamic load balancing schemes have been proposed throughout the years. However, most of these approaches require runtime dynamic […]

High Performance Computing (HPC) systems are nowadays more and more heterogeneous. Different processor types can be found on a single node including accelerators such as Graphics Processing Units (GPUs). To cope with the challenge of programming such complex systems, this work presents a domain-specific approach to automatically generate code tailored to different processor types. Low-level […]

The use of general-purpose computing on a GPU is an effective way to accelerate the FDTD method. This paper introduces flexibility to the theoretically best available approach. It examines the performance on both Tesla- and Fermi-architecture GPUs, and identifies the best way to determine the GPU parameters for the proposed method.

We investigate multi-level parallelism on GPU clusters with MPI-CUDA and hybrid MPI-OpenMP-CUDA parallel implementations, in which all computations are done on the GPU using CUDA. We explore efficiency and scalability of incompressible flow computations using up to 256 GPUs on a problem with approximately 17.2 billion cells. Our work addresses some of the unique issues […]

We investigate efficient algorithmic realisations for robust deconvolution of grey-value images with known space-invariant point-spread function, with emphasis on 1D motion blur scenarios. The goal is to make deconvolution suitable as preprocessing step in automated image processing environments with tight time constraints. Candidate deconvolution methods are selected for their restoration quality, robustness and efficiency. Evaluation […]