high performance computing on graphics processing units: hgpu.org

This paper presents an effective scheme for clustering a huge data set using a commodity programmable graphics processing unit(GPU). Due to GPUs application-specific architecture, one of the current research issues is how to bind the rendering pipeline with the data-clustering process. By taking advantage of GPUs parallel processing capability, our implementation scheme is devised to […]

The graphics processing unit (GPU) has evolved from a single-purpose graphics accelerator to a tool that can greatly accelerate the performance of high-performance computing (HPC) applications. Previous studies have shown that discrete GPUs, while energy efficient for compute-intensive scientific applications, consume very high power. In fact, a compute-capable discrete GPU can draw more than 200 […]

We report on our experience with integrating and using graphics processing units (GPUs) as fast parallel floating-point co-processors to accelerate two fundamental computational scientific kernels on the GPU: sparse direct factorization and nonlinear interior-point optimization. Since a full re-implementation of these complex kernels is typically not feasible, we identify the matrix-matrix multiplication as a first […]

In this paper we take a look at GPU-Quicksort, an efficient Quicksort algorithm suitable for the highly parallel multi-core graphics processors. Quicksort had previously been considered an inefficient sorting solution for graphics processors, but GPU-Quicksort often performs better than the fastest known sorting implementations for graphics processors, such as radix and bitonic sort. Quicksort can […]

Graphics processing units (GPUs), originally developed for rendering real-time effects in computer games, now provide unprecedented computational power for scientific applications. In this paper, we develop a general purpose molecular dynamics code that runs entirely on a single GPU. It is shown that our GPU implementation provides a performance equivalent to that of fast 30 […]

A leading-order, leading-color parton-level event generator is developed for use on a multi-threaded GPU. Speed-up factors between 150 and 300 are obtained compared to an unoptimized CPU-based implementation of the event generator. In this first paper we study the feasibility of a GPU-based event generator with an emphasis on the constraints imposed by the hardware. […]

A graphic processing unit (GPU) implementation of the multicomponent lattice Boltzmann equation with multirange interactions for soft-glassy materials [“glassy” lattice Boltzmann (LB)] is presented. Performance measurements for flows under shear indicate a GPU/CPU speed up in excess of 10 for 1024 2 grids. Such significant speed up permits to carry out multimillion time-steps simulations of […]

Deep shadow maps unify the computation of volumetric and geometric shadows. For each pixel in the shadow map, a fractional visibility function is sampled, pre-filtered, and compressed as a piecewise linear function. However, the original implementation targets software-based off-line rendering. Similar previous algorithms on GPUs focus on geometric shadows and lose many important benefits of […]

Despite the recent advances in graphics hardware capabilities, a brute force approach is incapable of interactively displaying terabytes of data. We have implemented a system that uses hierarchical level-of-detailing for the results of cosmological simulations, in order to display visually accurate results without loading in the full dataset (containing over 10 billion points). The guiding […]

In this paper, we introduce an innovative CNN algorithm development environment that significantly assists algorithmic design. The introduced graphical user interface uses Matlab Simulink with UMF-like program description, where direct functionality accompanies better accessability. The new generation of graphical cards incorporate many general purpose graphics processing units, giving the power of parallel computing to a […]

In this paper we describe a GPU parallelization of the 3D finite difference computation using CUDA. Data access redundancy is used as the metric to determine the optimal implementation for both the stencil-only computation, as well as the discretization of the wave equation, which is currently of great interest in seismic computing. For the larger […]

Sorting is a well-investigated topic in Computer Science in general and by now many efficient sorting algorithms for CPUs and GPUs have been developed. There is no swapping, paging, etc. available on GPUs to provide more virtual memory than physically available, thus if one wants to sort sequences that exceed GPU memory using the GPU […]