high performance computing on graphics processing units: hgpu.org

Spectral mixture analysis is an important task for remotely sensed hyperspectral data interpretation. In spectral unmixing, both the determination of spectrally pure signatures (endmembers) and the unmixing process that interprets mixed pixels as combinations of endmembers are computationally expensive procedures. An exciting recent development in the field of commodity computing is the emergence of programmable […]

A holographic fringe pattern generation methods is based on Fraunhofer diffraction and subsequent segmentation and approximation of the fringe pattern. Several modifications of the original algorithm are already proposed to improve the quality of reconstructions. We compare the quality of to the reconstructed images from different versions of this algorithm by taking the reconstructions from […]

Application of the GPU to the computer generated holography is a topic of research for some time. While the majority of authors aim on performance, we aim on visual aspects. We present a new approach that is capable to synthesise a hologram of a scene described by triangles using the GPU and it is capable […]

In recent years the the potential and programmability of Graphics Processing Units (GPU) has raised a note-worthy interest in the research community for applications that demand high-computational power. In particular, in financial applications containing thousands of high-dimensional samples, machine learning techniques such as neural networks are often used. One of their main limitations is that […]

The radiosity method permits the obtaining of high quality images through the evaluation of the global illumination of the scene. The computational complexity and the memory requirements of the algorithm are the main problems when a large scene has to be processed. To reduce the memory requirements, Monte Carlo radiosity method is often used. In […]

Emerging GPU architectures for high performance computing are well suited to a data-parallel programming model. This paper presents preliminary work examining a programming methodology that provides Fortran programmers with access to these emerging systems. We use array constructs in Fortran to show how this infrequently exploited, standardized language feature is easily transformed to lower-level accelerator […]

The identification, and subsequent discovery, of fast radio transients through blind-search surveys requires a large amount of processing power, in worst cases scaling as $mathcal{O}(N^3)$. For this reason, survey data are generally processed offline, using high-performance computing architectures or hardware-based designs. In recent years, graphics processing units have been extensively used for numerical analysis and […]

Modern graphics processing units (GPU) are used for much more than simply 3D graphics applications. From machine vision to finite element analysis, CPU’s are being used in diverse applications, collectively called general purpose graphics processor utilization. This paper explores the capabilities and limitations of modern GPU’s and surveys the neural computation technologies that have been […]

We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimise data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximises parallelism and tries to hide access latencies. We apply […]

To foster innovative uses of micro-ultrasound in biomedicine, it is beneficial to develop flexible research-purpose systems that allow researchers to easily reconfigure its system-level operations such as transmit firing sequence and receive processing. In this paper, we present the development of a programmable micro-ultrasound research platform that is capable of realizing various micro-imaging algorithms. The […]

The search techniques audio content MIR (music information retrieval) face two major challenges: the robustness of the algorithm and the speed of this operation. In this article proposes a model of fast algorithm for the extraction of audio data by the fingerprinting technique, which is implemented on a CPU-based platform and then parallelized to run […]

Feature detectors are schemes that locate and describe points or regions of ‘interest’ in an image. Today there are numerous machine vision applications needing efficient feature detectors that can work on Real-time; moreover, since this detection is one of the most time consuming tasks in several vision devices, the speed of the feature detection schemes […]