high performance computing on graphics processing units: hgpu.org

CONTEXT. The cryptographically secure pseudo-random number generator Blum Blum Shub (BBS) is a simple algorithm with a strong security proof, however it requires very large numbers to be secure, which makes it computationally heavy. The Graphics Processing Unit (GPU) is a common vector processor originally dedicated to computer-game graphics, but has since been adapted to […]

Graphics Processing Unit (GPU) has been converted to general purpose parallel processor devices from a single rendering. It performed far better than the CPU in many fields of science. String matching is widely used, especially in information retrieval, intrusion detection, Computational Biology etc. In this paper, we designed and implemented a GPU-based multi-string matching algorithm […]

High-performance computing systems today include a variety of compute devices such as multi-core CPUs, GPUs and many-core accelerators. OpenCL allows programming different types of compute devices using a single API and kernel language. However, there is no standard matrix operations library in OpenCL for operations such as matrix multiplication that works well on a variety […]

An algorithm is proposed for tracking objects in real time. The algorithm is based on neural network implemented on GPU. Investigation and parameter optimization of the algorithm are realized. Tracking process has accelerated by 10 times and the training process has accelerated by 2 times versus to the sequential algorithm version. The maximum resolution of […]

Swarm intelligence algorithms have been widely used to solve difficult real world problems in both academic and engineering domains. Thanks to the inherent parallelism, various parallelized swarm intelligence algorithms have been proposed to speed up the optimization process, especially on the massively parallel processing architecture GPUs. However, conventional swarm intelligence algorithms are usually not designed […]

Computing highly-accurate approximate solutions to partial differential equations (PDEs) requires both a robust numerical method and a powerful machine. We present a parallel implementation of the discontinuous Galerkin (DG) method on graphics processing units (GPUs). In addition to being flexible and highly accurate, DG methods accommodate parallel architectures well, as their discontinuous nature produces entirely […]

Modern radio telescopes, such as the Low Frequency Array (LOFAR) in the north of the Netherlands, process the signal from the sky in software rather than expensive special purpose hardware, This gives the astronomers an unprecedented flexibility to perform a vast amount of various scientific experiments. However, designing the actual software that would give optimal […]

Three-dimensional simulations of buoyancy-driven flow of two immiscible liquids are performed using lattice Boltzmann method (LBM) implemented on a graphics processing unit (GPU). Graphics processing unit is a new paradigm for computing fluid flows and has become more popular in the recent years. It is a powerful and convenient to use. LBM, which is an […]

Matrix multiplication is a commonly-used mathematical operation that has many practical applications. It is used to solve a number of problems in a wide variety of fields including science, engineering, and computer science. Given two matrices, A and B, and a resultant matrix C. The concept of density is used to describe the number of […]

With the raise of cloud computing infrastructures on one side and the increased accessibility of parallel computational devices on the other, such as GPUs and multi-core CPUs, parallel programming has recently gained a renewed interest. This is particularly true in the domain of video coding, where the complexity and time consumption of the algorithms tend […]

Clusters of heterogeneous nodes composed of multi-core CPUs and GPUs are increasingly being used for High Performance Computing (HPC) due to the benefits in peak performance and energy efficiency. In order to fully harvest the computational capabilities of such architectures, application developers often employ a combination of different parallel programming paradigms (e.g. OpenCL, CUDA, MPI […]

The Parallel Proximal Algorithm (PPXA+) has been recently introduced as an efficient tool for solving convex optimization problems. It has proved particularly effective in the context of stereo vision, used as the methodological core of a novel disparity estimation technique. In this work, the main methodological issues limiting the efficient parallelization of this technique are […]