high performance computing on graphics processing units: hgpu.org

The objective of this thesis is to compare the suitability of FPGAs, GPUs and DSPs for digital image processing applications. Normalized cross-correlation is used as a benchmark, because this algorithm includes convolution, a common operation in image processing and elsewhere. Normalized cross-correlation is a template matching algorithm that is used to locate predefined objects in […]

We describe a multi-GPU implementation of the Ludwig application, which specialises in simulating of a variety of complex fluids via lattice Boltzmann fluid dynamics coupled to additional physics describing complex fluid constituents. We describe our methodology in augmenting the original CPU version with GPU functionality in a maintainable fashion. We present several optimisations that maximize […]

The heterogeneous parallel computing era has been accompanied by an ever-increasing number of disparate programming models. As a result, improving performance via heterogeneous computing is currently very challenging for application programmers. Domain-specific languages (DSLs) are a potential solution to this problem, as they can provide productivity, performance, and portability within the confines of a specific […]

Graphics Processing Units (GPUs) are high performance co-processors originally intended to improve the use and quality of computer graphics applications. Since researchers and practitioners realized the potential of using GPU for general purpose, their application has been extended to other fields out of computer graphics scope. The main objective of this paper is to evaluate […]

Real time processing for teamwork action recognition is a challenge, due to complex computational models to achieve high system performance. Hence, this paper proposes a framework based on Graphical Processing Units (GPUs) to achieve a significant speed up in the performance of role based activity recognition of teamwork. The framework can be applied in various […]

In wireless sensor network, when these sensors are wrongly placed in an observation region, they can quickly run out of batteries or be disconnected. These incidents may result in huge losses in terms of sensing data from numerous sensors and their costs. For this reason, a number of simulators have been developed as tools for […]

This works focuses on the Hough transform (HT). The HT is mostly used for the detection of lines or curves, but was also generalized for detection of arbitrary shapes. The main theme of this work are line parameterizations, especially the Point-to-Line mappings. These parameterizations share the property, that a point in the image maps onto […]

Medical imaging in hospitals requires fast and efficient image compression to support the clinical work flow and to save costs. Leastsquares autoregressive pixel prediction methods combined with arithmetic coding constitutes the state of the art in lossless image compression. However, a high computational complexity of both prevents the application of respective CPU implementations in practice. […]

We present an OCaml GPGPU library with a DSL embedded into OCaml to express GPGPU kernels. The level of performance achieved is measured through different examples. We also discuss the use of GPGPU programming to increase the performance of multicore-CPUs software, written in OCaml.

In this paper, we discuss parameter identification for models based on ordinary differential equations in the context of solid oxide fuel cells. In this case, verified methods (e.g. interval analysis), which provide a guarantee of correctness for the computed result, can be of great help for dealing with the appearing uncertainty and for devising accurate […]

In the field of Tracking and Data Fusion most, if not all, computations executed by a computer are carried out serially. The sole part of the process that is not entirely serial is the collection of data from multiple sensors, which can be executed in parallel. However, once the data is to be filtered the […]

Many emerging online data analysis applications require Large-scale streams data processing. GPU cluster is becoming a significantly parallel computing scheme to handling large-scale streams data tasks. However power optimization is a challenging issue. In this paper, we present a novel power consumption control model to shift power budge among nodes in the cluster based on […]