Heurísticas bioinspiradas para el problema de Floorplanning 3D térmico de dispositivos MPSoCs

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, leída el 20-06-2013Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu

Numerical simulation of non-Newtonian fluid flow in mixing geometries

In this thesis, a theoretical investigation is undertaken into fluid and mixing flows generated by various geometries for Newtonian and non-Newtonian fluids, on both sequential and parallel computer systems. The thesis begins by giving the necessary background to the mixing process and a summary of the fundamental characteristics of parallel architecture machines. This is followed by a literature review which covers accomplished work in mixing flows, numerical methods employed to simulate fluid mechanics problems and also a review of relevant parallel algorithms. Next, an overview is given of the numerical methods that have been reviewed, discussing the advantages and disadvantages of the different methods. In the first section of the work the implementation of the primitive variable finite element method to solve a simple two dimensional fluid flow problem is studied. For the same geometry colour band mixing is also investigated. Further investigational work is undertaken into the flows generated by various rotors for both Newtonian and non-Newtonian fluids. An extended version of the primitive variable formulation is employed, colour band mixing is also carried out on two of these geometries. The latter work is carried out on a parallel architecture machine. The design specifications of a parallel algorithm for a MIMD system are discussed, with particular emphasis placed on frontal and multifrontal methods. This is followed by an explanation of the implementation of the proposed parallel algorithm, applied to the same fluid flow problems as considered earlier and a discussion of the efficiency of the system is given. Finally, a discussion of the conclusions of the entire accomplished work is presented. A number of suggestions for future work are also given. Three published papers relating to the work carried out on the transputer networks are included in the appendices

Automatic visual recognition using parallel machines

Invariant features and quick matching algorithms are two major concerns in the area of automatic visual recognition. The former reduces the size of an established model database, and the latter shortens the computation time. This dissertation, will discussed both line invariants under perspective projection and parallel implementation of a dynamic programming technique for shape recognition. The feasibility of using parallel machines can be demonstrated through the dramatically reduced time complexity. In this dissertation, our algorithms are implemented on the AP1000 MIMD parallel machines. For processing an object with a features, the time complexity of the proposed parallel algorithm is O(n), while that of a uniprocessor is O(n2). The two applications, one for shape matching and the other for chain-code extraction, are used in order to demonstrate the usefulness of our methods. Invariants from four general lines under perspective projection are also discussed in here. In contrast to the approach which uses the epipolar geometry, we investigate the invariants under isotropy subgroups. Theoretically speaking, two independent invariants can be found for four general lines in 3D space. In practice, we show how to obtain these two invariants from the projective images of four general lines without the need of camera calibration. A projective invariant recognition system based on a hypothesis-generation-testing scheme is run on the hypercube parallel architecture. Object recognition is achieved by matching the scene projective invariants to the model projective invariants, called transfer. Then a hypothesis-generation-testing scheme is implemented on the hypercube parallel architecture

Real Time Log Length Measurement Using GPU Accelerated Visual Odometry

This thesis studies GPU accelerated visual odometry in measuring log length. The visual odometry would not suffer slippage nor require recalibration depending type of wood or temperature conditions compared to mechanical measurement. The requirement of the real-time performance is quite high. Image capturing in 120 Hz frequency is needed as log is moved several meters per second by harvester heads. Here GPU acceleration will be used as it can give speedup in magnitude of hundreds or more. Real-time performance is targeted by selecting fast algorithms for subtasks of measurement pipeline and considering possibilities to parallelize algorithm. In many cases performance boost is achieved, but not in expected magnitude. Physical constraints of the graphics card hardware become easily the limiting factor in parallelization. Real-time performance was achieved in this thesis but not with required accuracy. It remained for future work to find out which algorithms would give both targets.  Taman lisensiaatintutkimuksen aiheena on GPU laskennan kaytto konenäköön perustuvassa tukin pituuden mittauksessa. Konenäköön perustuva pituuden mittaus ei tarvitse uudelleen kalibrointia puulajin tai lämpötilan mukaan. Konenäköön perustuvassa mittauksessa myöskaan mittapyöra ei voi luistaa tukin pinnalla. Realiaikaisuuden vaatimus on tässä sovelluksessa korkea. Kuvat on otettu 120 Hz taajuudella, koska leikkuupää liikuttaa tukkia useita metrejä sekunnissa. GPU laskenta potentiaalisesti nopeuttaisi laskentaa tarvittavissa määrin. Realiaikaista vastetta haettiin seka algoritmien valinnalla etta harkitsemalla mahdollisuuksia rinnaisohjelmoinnin käyttämiseen. Monessa tapauksessa vasteet paranivat, vaikka grafiikkakortin ominaisuudet usein rajoittivat rinnaikkaisohjelmoinnista saatavaa hyötyä. Realiaikainen vaste saavutettiin, mutta ei tarvittavalla pituuden mittaamisen tarkkuudella. Molempien tavoitteiden saavuttaminen jai mahdollisten jatkotöiden tehtäväksi