high performance computing on graphics processing units: hgpu.org

Spatial data partitioning techniques are important for obtaining fast and efficient simulations of N-Body particle and spatial agent based models where they considerably reduce redundant entity interaction computation times. Highly parallel techniques based on concurrent threading can be deployed to further speed up such simulations. We study the use of GPU accelerators and highly data […]

General purpose graphic programming unit (GPGPU) programming is a novel approach for solving parallel variable independent problems. The graphic processor core (GPU) gives the possibility to use multiple blocks, each of which contains hundreds of threads. Each of these threads can be visualized as a core onto itself, and tasks can be simultaneously sent to […]

Graphic processing units (GPUs) are powerful graphics engines featuring high levels of parallelism and extreme memory bandwidth, which constitute a powerful computing platform to solve complex problems involving chemically reacting flows. In the present study, computer programs for combustion simulations with detailed chemical kinetic mechanisms were compiled in the Compute Unified Device Architecture (CUDA) language […]

A novel algorithm is presented to compute the convex hull of a point set in R3using the graphics processing unit (GPU). By exploiting the relationship between the Voronoi diagram and the convex hull, the algorithm derives the approximation of the convex hull from the former. The missed points are found back by using a two-round […]

Radiation-hardened processors are designed to be resilient against soft errorsbut such processors are slower than Commercial Off-The-Shelf (COTS)processors as well significantly costlier. In order to mitigate the high costs,software techniques such as task re-executions must be deployed together withadequately hardened processors to provide reliability. This leads to a huge designspace comprising of the hardening level […]

Modern computer processing units tend towards simpler cores in greater numbers, favouring the development of data-parallel applications. Evolutionary algorithms are ideal for taking full advantage of SIMD (Single Instruction, Multiple Data) processing, which is available on both CPUs and GPUs. Creating software that runs on a GPU requires the use of specialised programming languages or […]

General purpose computing on graphics processing units (GPGPU) consists of using GPUs to handle computations commonly handled by CPUs. GPGPU programming implies developing specific programs to run on GPUs managed by a host program running on the CPU. To achieve high performance implies to explicitly organize memory transfers between devices. Besides, different incompatible frameworks exist […]

We describe the problem of parallelization of finite difference method (FDM) and finite element method (FEM) computations for certain class of partial differential equations (PDEs) on High Performance Computing (HPC) GPU cluster. For FDM, the structured grids have been employed and optimal data rearrangement operations are performed in GPU computations. For FEM, unstructured triangular and […]

LSQR (Sparse Equations and Least Squares) is a widely used Krylov subspace method to solve large-scale linear systems in seismic tomography. This paper presents a parallel MPI-CUDA implementation for LSQR solver. On CUDA level, our contributions include: (1) utilize CUBLAS and CUSPARSE to compute major steps in LSQR; (2) optimize memory copy between host memory […]

The Heisenberg model of classical spins makes use of both Monte Carlo stochastic dynamics as well as time-integration of its equation of motion. These two schemes have different parallelisation strategies and tradeoffs. We implement both algorithms using a data-parallel approach for Graphical Processing Units (GPUs) and we discuss the resulting performance on various combinations of […]

The aim of the present paper is to report on our recent results for GPU accelerated simulations of compressible flows. For numerical simulation the adaptive discontinuous Galerkin method with the multidimensional bicharacteristic based evolution Galerkin operator has been used. For time discretization we have applied the explicit third order Runge-Kutta method. Evaluation of the genuinely […]

Computer systems increasingly integrate heterogeneous computing elements like graphic processing units and specialized co-processors. The systematic programming and exploitation of such heterogeneous systems is still a subject of research. While many efforts address the programming of accelerators, scheduling heterogeneous systems, i. e., mapping parts of an application to accelerators at runtime, is still performed from […]