high performance computing on graphics processing units: hgpu.org

Multiple-input multiple-output (MIMO) is an existing technique that can significantly increase throughput of the system by employing multiple antennas at the transmitter and the receiver. Realizing maximum benefit from this technique requires computationally intensive detectors which poses significant challenges to receiver design. Furthermore, a flexible detector or multiple detectors are needed to handle different configurations. […]

The letter discusses a fast implementation of the conjugate gradient iterative method with E-field multilevel preconditioner applied to solving real symmetric and sparse systems obtained with vector finite element method. In order to accelerate computations, a graphics processing unit (GPU) was used and significant speed-up (2.61 fold) was achieved comparing to a central processing unit […]

We present a multi-resolution mesh model of the ocean surface based on a straightforward terrain LOD scheme, tiled quad-tree, with that the region of ocean surface can be extended limitlessly and readily adapted for GPU acceleration. We have introduced the concept of wrapped fractal surface (WFS) for generating height field map of the ocean. Through […]

In this thesis a soft processor programming model and architecture is proposed that is inspired by graphics processing units (GPUs) and well-matched to the strengths of FPGAs, namely highly-parallel and pipelinable computation. The proposed soft processor architecture exploits multithreading, vector operations, and predication to supply a floating-point pipeline of up to 60 stages via hardware […]

There is building interest in using FPGAs as accelerators for high-performance computing, but existing systems for programming them are so far inadequate. In this paper we propose a soft processor programming model and architecture inspired by graphics processing units (GPUs) that are well-matched to the strengths of FPGAs, namely highly-parallel and pipelinable computation. In particular, […]

In this paper, we employ the programmable graphics processing unit (GPU) to accelerate the IPO computation for analyzing the scattering of open cavities. Since the iterative strategy accounts for multiple reflections on the inner wall, the IPO method provides a more accurate solution than the other high frequency asymptotic methods. However, it suffers from a […]

This article presents the details about the acceleration of 2D wavelet-based medical data (image) compression on MATLAB with CUDA. It is obvious that the diagnostic materials (mostly as acertain type of image) are increasingly acquired in a digital format. Therefore, common need to daily manipulate huge amount of data brought about the issue of compression […]

Cellular automata are a well-known modeling formalism exploited in a wide range of application areas. In many of those, the complexity of models hampers a thorough analysis of the system under study. Therefore, efficient simulation algorithms are required. We present here a comparison of seven different simulation algorithms for cellular automata: the classical ldquofullrdquo simulator, […]

Current imaging experiments at synchrotron beam lines often lack a real-time data assessment. X-ray imaging cameras installed at synchrotron facilities like ANKA provide millions of pixels, each with a resolution of 12 bits or more, and take up to several thousand frames per second. A given experiment can produce data sets of multiple gigabytes in […]

ID shadow-maps are used for robust real-time rendering of shadows. The primary disadvantage of using shadow-maps is their excessive size for large scenes in case high quality shadows are needed. To eliminate large memory requirements and texture-size limitations of the current generation GPUs, texture compression is an important tool. We present a framework where compressed […]

Remotely sensed hyperspectral imaging instruments provide high-dimensional data containing rich information in both the spatial and the spectral domain. In many surveillance applications, detecting objects (targets) is a very important task. In particular, algorithms for detecting (moving or static) targets, or targets that could expand their size (such as propagating fires) often require timely responses […]

We present a biologically motivated classifier and feature descriptors that are designed for execution on single instruction multi data hardware and are applied to high speed multiclass object recognition. Our feature extractor uses a cellular tuning approach to select the optimal Gabor filters to process a given input, followed by the computation of scale and […]