Video Processing Acceleration using Reconfigurable Logic and Graphics Processors

A vexing question is `which architecture will prevail as the core feature of the next state of the art video processing system?' This thesis examines the substitutive and collaborative use of the two alternatives of the reconfigurable logic and graphics processor architectures. A structured approach to executing architecture comparison is presented - this includes a proposed `Three Axes of Algorithm Characterisation' scheme and a formulation of perfor- mance drivers. The approach is an appealing platform for clearly defining the problem, assumptions and results of a comparison. In this work it is used to resolve the advanta- geous factors of the graphics processor and reconfigurable logic for video processing, and the conditions determining which one is superior. The comparison results prompt the exploration of the customisable options for the graphics processor architecture. To clearly define the architectural design space, the graphics processor is first identifed as part of a wider scope of homogeneous multi-processing element (HoMPE) architectures. A novel exploration tool is described which is suited to the investigation of the customisable op- tions of HoMPE architectures. The tool adopts a systematic exploration approach and a high-level parameterisable system model, and is used to explore pre- and post-fabrication customisable options for the graphics processor. A positive result of the exploration is the proposal of a reconfigurable engine for data access (REDA) to optimise graphics processor performance for video processing-specific memory access patterns. REDA demonstrates the viability of the use of reconfigurable logic as collaborative `glue logic' in the graphics processor architecture

Multiscale, Multiphysics Modelling of Coastal Ocean Processes: Paradigms and Approaches

This Special Issue includes papers on physical phenomena, such as wind-driven flows, coastal flooding, and turbidity currents, and modeling techniques, such as model comparison, model coupling, parallel computation, and domain decomposition. These papers illustrate the need for modeling coastal ocean flows with multiple physical processes at different scales. Additionally, these papers reflect the current status of such modeling of coastal ocean flows, and they present a roadmap with numerical methods, data collection, and artificial intelligence as future endeavors

Homology sequence analysis using GPU acceleration

A number of problems in bioinformatics, systems biology and computational biology field require abstracting physical entities to mathematical or computational models. In such studies, the computational paradigms often involve algorithms that can be solved by the Central Processing Unit (CPU). Historically, those algorithms benefit from the advancements of computing power in the serial processing capabilities of individual CPU cores. However, the growth has slowed down over recent years, as scaling out CPU has been shown to be both cost-prohibitive and insecure. To overcome this problem, parallel computing approaches that employ the Graphics Processing Unit (GPU) have gained attention as complementing or replacing traditional CPU approaches. The premise of this research is to investigate the applicability of various parallel computing platforms to several problems in the detection and analysis of homology in biological sequence. I hypothesize that by exploiting the sheer amount of computation power and sequencing data, it is possible to deduce information from raw sequences without supplying the underlying prior knowledge to come up with an answer. I have developed such tools to perform analysis at scales that are traditionally unattainable with general-purpose CPU platforms. I have developed a method to accelerate sequence alignment on the GPU, and I used the method to investigate whether the Operational Taxonomic Unit (OTU) classification problem can be improved with such sheer amount of computational power. I have developed a method to accelerate pairwise k-mer comparison on the GPU, and I used the method to further develop PolyHomology, a framework to scaffold shared sequence motifs across large numbers of genomes to illuminate the structure of the regulatory network in yeasts. The results suggest that such approach to heterogeneous computing could help to answer questions in biology and is a viable path to new discoveries in the present and the future.Includes bibliographical reference

Towards Cognition-Guided Patient-Specific Numerical Simulation for Cardiac Surgery Assistance

Motivation. Patient-specific, knowledge-based, holistic surgical treatment planning is of utmost importance when dealing with complex surgery. Surgeons need to account for all available medical patient data, keep track of technical developments, and stay on top of current surgical expert knowledge to define a suitable surgical treatment strategy. There is a large potential for computer assistance, also, and in particular, regarding surgery simulation which gives surgeons the opportunity not only to plan but to simulate, too, some steps of an intervention and to forecast relevant surgical situations. Purpose. In this work, we particularly look at mitral valve reconstruction (MVR) surgery, which is to re-establish the functionality of an incompetent mitral valve (MV) through implantation of an artificial ring that reshapes the valvular morphology. We aim at supporting MVR by providing surgeons with biomechanical FEM-based MVR surgery simulations that enable them to assess the simulated behavior of the MV after an MVR. However, according to the above requirements, such surgery simulation is really beneficial to surgeons only if it is patient-specific, surgical expert knowledge-based, comprehensive in terms of the underlying model and the patient’s data, and if its setup and execution is fully automated and integrated into the surgical treatment workflow. Methods. This PhD work conducts research on simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance. First, we derive a biomechanical MV/MVR model and develop an FEM-based MVR surgery simulation using the FEM software toolkit HiFlow3. Following, we outline the functionality and features of the Medical Simulation Markup Language (MSML) and how it simplifies the biomechanical modeling workflow. It is then detailed, how, by means of the MSML and a set of dedicated MVR simulation reprocessing operators, patient-individual medical data can comprehensively be analyzed and processed in order for the fully automated setup of MVR simulation scenarios. Finally, the presented work is integrated into the cognitive system architecture of the joint research project Cognition-Guided Surgery. We particularly look at its semantic knowledge and data infrastructure as well as at the setup of its cognitive software components, which eventually facilitate cognition-guidance and patient-specifity for the overall simulation-enhanced MVR assistance pipeline. Results and Discussion. We have proposed and implemented, for the first time, a prototypic system for simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance. The overall system was evaluated in terms of functionality and performance. Through its cognitive, data-driven pipeline setup, medical patient data and surgical information is analyzed and processed comprehensively, efficiently and fully automatically, and the hence set-up simulation scenarios yield reliable, patient-specific MVR surgery simulation results. This indicates the system’s usability and applicability. The proposed work thus presents an important step towards a simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance, and can – once operative – be expected to significantly enhance MVR surgery. Concluding, we discuss possible further research contents and promising applications to build upon the presented work

Closing the loop by engineering consistent 4D seismic to simulator inversion

The multi-disciplinary nature of closing the loop (CtL) between 4D seismic and reservoir engineering data requires integrated workflows to make sense of these different measurements. According to the published literatures, this integration is subject to significant inconsistency and uncertainty. To resolve this, an engineering consistent (EC) concept is proposed that favours an orderly workflow to modelling and inverting the 4D seismic response. Establishing such consistency facilitates a quantitative comparison between the reservoir model and the acquired 4D seismic data observation. With respect to the sim2seis workflow developed by Amini (2014), a corresponding inverse solution is proposed. The inversion, called seis2sim, utilises the model prediction as a priori information, searching for EC seismic answers in the joint domain between reservoir engineering and geophysics. Driven by a Bayesian algorithm, the inversion delivers more stable and certain elastic parameters upon application of the EC constraints. The seis2sim approach is firstly tested with a synthetic example derived from a real dataset before being applied to the Heidrun and Girassol field datasets. The two real data examples are distinctive from each other in terms of seismic quality, geological nature and production activities. After extracting the 3D and 4D impedance from the seismic data, CtL workflows are designed to update various aspects of the reservoir model according to the comparison between sim2seis and seis2sim. The discrepancy revealed by this cross-domain comparison is informative for robust updating of the reservoir model in terms reservoir geometry, volumetrics and connectivity. After applying tailored CtL workflows to the Heidrun and Girassol datasets, the statistical istributions of petrophysical parameters, such as porosity and NTG, as well as intra- and inter-connectivity for reservoir compartments are revised accordingly. Consequently, the 3D and 4D seismic responses of the reservoir models are assimilated with the observations, while the production match to the historical data is also improved . Overall, the proposed seis2sim and CtL workflows show a progression in the quantitative updating of the reservoir models using time-lapse seismic data

Research Reports: 1997 NASA/ASEE Summer Faculty Fellowship Program

For the 33rd consecutive year, a NASA/ASEE Summer Faculty Fellowship Program was conducted at the Marshall Space Flight Center (MSFC). The program was conducted by the University of Alabama in Huntsville and MSFC during the period June 2, 1997 through August 8, 1997. Operated under the auspices of the American Society for Engineering Education, the MSFC program was sponsored by the Higher Education Branch, Education Division, NASA Headquarters, Washington, D.C. The basic objectives of the program, which are in the 34th year of operation nationally, are: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA centers. The Faculty Fellows spent 10 weeks at MSFC engaged in a research project compatible with their interests and background and worked in collaboration with a NASA/MSFC colleague. This document is a compilation of Fellows' reports on their research during the summer of 1997. The University of Alabama in Huntsville presents the Co-Directors' report on the administrative operations of the program. Further information can be obtained by contacting any of the editors

Massively parallel time- and frequency-domain Navier-Stokes Computational Fluid Dynamics analysis of wind turbine and oscillating wing unsteady flows

Increasing interest in renewable energy sources for electricity production complying with stricter environmental policies has greatly contributed to further optimisation of existing devices and the development of novel renewable energy generation systems. The research and development of these advanced systems is tightly bound to the use of reliable design methods, which enable accurate and efficient design. Reynolds-averaged Navier-Stokes Computational Fluid Dynamics is one of the design methods that may be used to accurately analyse complex flows past current and forthcoming renewable energy fluid machinery such as wind turbines and oscillating wings for marine power generation. The use of this simulation technology offers a deeper insight into the complex flow physics of renewable energy machines than the lower-fidelity methods widely used in industry. The complex flows past these devices, which are characterised by highly unsteady and, often, predominantly periodic behaviour, can significantly affect power production and structural loads. Therefore, such flows need to be accurately predicted. The research work presented in this thesis deals with the development of a novel, accurate, scalable, massively parallel CFD research code COSA for general fluid-based renewable energy applications. The research work also demonstrates the capabilities of newly developed solvers of COSA by investigating complex three-dimensional unsteady periodic flows past oscillating wings and horizontal-axis wind turbines. Oscillating wings for the extraction of energy from an oncoming water or air stream, feature highly unsteady hydrodynamics. The flow past oscillating wings may feature dynamic stall and leading edge vortex shedding, and is significantly three-dimensional due to finite-wing effects. Detailed understanding of these phenomena is essential for maximising the power generation efficiency. Most of the knowledge on oscillating wing hydrodynamics is based on two-dimensional low-Reynolds number computational fluid dynamics studies and experimental testing. However, real installations are expected to feature Reynolds numbers of the order of 1 million and strong finite-wing-induced losses. This research investigates the impact of finite wing effects on the hydrodynamics of a realistic aspect ratio 10 oscillating wing device in a stream with Reynolds number of 1.5 million, for two high-energy extraction operating regimes. The benefits of using endplates in order to reduce finite-wing-induced losses are also analyzed. Three-dimensional time-accurate Reynolds-averaged Navier-Stokes simulations using Menter's shear stress transport turbulence model and a 30-million-cell grid are performed. Detailed comparative hydrodynamic analyses of the finite and infinite wings highlight that the power generation efficiency of the finite wing with sharp tips for the considered high energy-extraction regimes decreases by up to 20 %, whereas the maximum power drop is 15 % at most when using the endplates. Horizontal-axis wind turbines may experience strong unsteady periodic flow regimes, such as those associated with the yawed wind condition. Reynolds-averaged Navier-Stokes CFD has been demonstrated to predict horizontal-axis wind turbine unsteady flows with accuracy suitable for reliable turbine design. The major drawback of conventional Reynolds-averaged Navier-Stokes CFD is its high computational cost. A time-step-independent time-domain simulation of horizontal-axis wind turbine periodic flows requires long runtimes, as several rotor revolutions have to be simulated before the periodic state is achieved. Runtimes can be significantly reduced by using the frequency-domain harmonic balance method for solving the unsteady Reynolds-averaged Navier-Stokes equations. This research has demonstrated that this promising technology can be efficiently used for the analyses of complex three-dimensional horizontal-axis wind turbine periodic flows, and has a vast potential for rapid wind turbine design. The three-dimensional simulations of the periodic flow past the blade of the NREL 5-MW baseline horizontal-axis wind turbine in yawed wind have been selected for the demonstration of the effectiveness of the developed technology. The comparative assessment is based on thorough parametric time-domain and harmonic balance analyses. Presented results highlight that horizontal-axis wind turbine periodic flows can be computed by the harmonic balance solver about fifty times more rapidly than by the conventional time-domain analysis, with accuracy comparable to that of the time-domain solver