high performance computing on graphics processing units: hgpu.org

In this article a strategy to accelerate the simulation and visualization of combined advective-diffusive mixing of a contaminant inside a square cavity with time-dependent boundary-conditions is presented. No moving walls are required to mix the fluid, but natural convection by periodic temperatures on opposite walls. A contaminant will diffuse asymptotically to uniform concentration. Advective mixing […]

Matching patches of a source image with patches of itself or a target image is a first step for many operations. Finding the optimum nearest-neighbors of each patch using a global search of the image is expensive. Optimality is often sacrificed for speed as a result. We present the Mixed-Resolution Patch-Matching (MRPM) algorithm that uses […]

We present a novel implementation of a dense, square, non-structured matrix factorization algorithm, namely the WZ factorization – with the use of graphics processors (GPUs) and CPUs to gain a high performance at a low cost. We rewrite this factorization as operations on blocks of matrices and vectors. We have implemented our block-vector algorithm on […]

This paper explores the opportunities of using a GPGPU to solve systems of polynomial equations. We propose numerical real root-finding based on recursive de Casteljau subdivision over an n-dimensional rectangular domain. Two variants of parallelism-multithreading and multiprocessing-have been investigated. The speed, memory consumption and resistance for different sets of input data have also been examined.

In this paper, we present an efficient implementation of parallel algorithms to remove noise in digital images using different Graphics Processing Units (GPUs). The algorithm, based on the concept of peer group, uses a fuzzy metric for finding wrong pixels and the Arithmetic Mean Filter (AMF) to correct it. There are many factors to study […]

As reconfigurable logic devices see increasing use in aerospace and terrestrial applications, fault tolerant techniques are being developed to counter rising susceptibility due to decreasing feature sizes. Applying fault-tolerance to an entire circuit induces unacceptable area and time penalties, thus some techniques trade area for fault tolerance. Area-Constrained Partial Fault Tolerance (ACPFT) is a methodology […]

The exploitation of heterogeneous resources is becoming increasingly important for general purpose computing. Unfortunately, heterogeneous systems require much more effort to be programmed than the traditional single or even multi-core computers most programmers are familiar with. Not only new concepts, but also new tools with different restrictions must be learned and applied. Additionally, many of […]

The simulation of Radiative Heat Transfer (RHT) effects by the Photon Monte Carlo (PMC) method is a computationally demanding problem. In this paper we present results and analysis of a new algorithm designed to solve this problem on a hybrid computing architecture. This architecture includes distributed memory, shared memory, and Graphics Processing Unit (GPU) accelerated […]

In this thesis, we present a framework for efficient analysis of large-scale network datasets. There are four important components in our framework: a) a high performance computing platform with Graphics Processing Units (GPUs) and efficient implementations of mining algorithms on top of the GPU platform. b) an efficient summarization method to compress the storage space […]

The aim of the paper is to show how to design fast parallel algorithms for linear congruential and lagged Fibonacci pseudorandom numbers generators. The new algorithms employ the divide-and-conquer approach for solving linear recurrence systems and can be easily implemented on GPU-accelerated hybrid systems using CUDA or OpenCL. Numerical experiments performed on a computer system […]

GPU/GPGPU computing has been used widely in scientific simulation to improve the performance on hybrid architectures. The quantum chemistry field has benefited greatly from using GPUs, including tasks such as visualization of molecular orbitals and computation of electronic structures. To gain significant success in using GPUs, a large amount of code rewriting and restructuring is […]

In this research, a Genetic Algorithms framework for Running On Parallel environments, which is named GAROP, is proposed. The GAROP provides the library for a parallel processing, so that users should only describe codes for genetic algorithms (GA) programs, utilizing the library implemented for the part requiring a parallel processing. In the GAROP framework, GA […]