855 resultados para Parallel Computation


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Singularities of robot manipulators have been intensely studied in the last decades by researchers of many fields. Serial singularities produce some local loss of dexterity of the manipulator, therefore it might be desirable to search for singularityfree trajectories in the jointspace. On the other hand, parallel singularities are very dangerous for parallel manipulators, for they may provoke the local loss of platform control, and jeopardize the structural integrity of links or actuators. It is therefore utterly important to avoid parallel singularities, while operating a parallel machine. Furthermore, there might be some configurations of a parallel manipulators that are allowed by the constraints, but nevertheless are unreachable by any feasible path. The present work proposes a numerical procedure based upon Morse theory, an important branch of differential topology. Such procedure counts and identify the singularity-free regions that are cut by the singularity locus out of the configuration space, and the disjoint regions composing the configuration space of a parallel manipulator. Moreover, given any two configurations of a manipulator, a feasible or a singularity-free path connecting them can always be found, or it can be proved that none exists. Examples of applications to 3R and 6R serial manipulators, to 3UPS and 3UPU parallel wrists, to 3UPU parallel translational manipulators, and to 3RRR planar manipulators are reported in the work.

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[EN]A new parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes is proposed in this paper. We provide a detailed analysis of its performance on shared-memory many-core computer architectures. This performance analysis includes the evaluation of execution time, parallel scalability, load balancing, and parallelism bottlenecks. Additionally, we compare the impact of three previously published graph coloring procedures on the performance of our parallel algorithm. We use six benchmark meshes with a wide range of sizes. Using these experimental data sets, we describe the behavior of the parallel algorithm for different data sizes. We demonstrate that this algorithm is highly scalable when it runs on two different high-performance many-core computers with up to 128 processors...

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In this work we introduce an analytical approach for the frequency warping transform. Criteria for the design of operators based on arbitrary warping maps are provided and an algorithm carrying out a fast computation is defined. Such operators can be used to shape the tiling of time-frequency plane in a flexible way. Moreover, they are designed to be inverted by the application of their adjoint operator. According to the proposed mathematical model, the frequency warping transform is computed by considering two additive operators: the first one represents its nonuniform Fourier transform approximation and the second one suppresses aliasing. The first operator is known to be analytically characterized and fast computable by various interpolation approaches. A factorization of the second operator is found for arbitrary shaped non-smooth warping maps. By properly truncating the operators involved in the factorization, the computation turns out to be fast without compromising accuracy.

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The 3-UPU three degrees of freedom fully parallel manipulator, where U and P are for universal and prismatic pair respectively, is a very well known manipulator that can provide the platform with three degrees of freedom of pure translation, pure rotation or mixed translation and rotation with respect to the base, according to the relative directions of the revolute pair axes (each universal pair comprises two revolute pairs with intersecting and perpendicular axes). In particular, pure translational parallel 3-UPU manipulators (3-UPU TPMs) received great attention. Many studies have been reported in the literature on singularities, workspace, and joint clearance influence on the platform accuracy of this manipulator. However, much work has still to be done to reveal all the features this topology can offer to the designer when different architecture, i.e. different geometry are considered. Therefore, this dissertation will focus on this type of the 3-UPU manipulators. The first part of the dissertation presents six new architectures of the 3-UPU TPMs which offer interesting features to the designer. In the second part, a procedure is presented which is based on some indexes, in order to allows the designer to select the best architecture of the 3-UPU TPMs for a given task. Four indexes are proposed as stiffness, clearance, singularity and size of the manipulator in order to apply the procedure.

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Hybrid technologies, thanks to the convergence of integrated microelectronic devices and new class of microfluidic structures could open new perspectives to the way how nanoscale events are discovered, monitored and controlled. The key point of this thesis is to evaluate the impact of such an approach into applications of ion-channel High Throughput Screening (HTS)platforms. This approach offers promising opportunities for the development of new classes of sensitive, reliable and cheap sensors. There are numerous advantages of embedding microelectronic readout structures strictly coupled to sensing elements. On the one hand the signal-to-noise-ratio is increased as a result of scaling. On the other, the readout miniaturization allows organization of sensors into arrays, increasing the capability of the platform in terms of number of acquired data, as required in the HTS approach, to improve sensing accuracy and reliabiity. However, accurate interface design is required to establish efficient communication between ionic-based and electronic-based signals. The work made in this thesis will show a first example of a complete parallel readout system with single ion channel resolution, using a compact and scalable hybrid architecture suitable to be interfaced to large array of sensors, ensuring simultaneous signal recording and smart control of the signal-to-noise ratio and bandwidth trade off. More specifically, an array of microfluidic polymer structures, hosting artificial lipid bilayers blocks where single ion channel pores are embededed, is coupled with an array of ultra-low noise current amplifiers for signal amplification and data processing. As demonstrating working example, the platform was used to acquire ultra small currents derived by single non-covalent molecular binding between alpha-hemolysin pores and beta-cyclodextrin molecules in artificial lipid membranes.

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The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

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This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.

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Parallel mechanisms show desirable characteristics such as a large payload to robot weight ratio, considerable stiffness, low inertia and high dynamic performances. In particular, parallel manipulators with fewer than six degrees of freedom have recently attracted researchers’ attention, as their employ may prove valuable in those applications in which a higher mobility is uncalled-for. The attention of this dissertation is focused on translational parallel manipulators (TPMs), that is on parallel manipulators whose output link (platform) is provided with a pure translational motion with respect to the frame. The first part deals with the general problem of the topological synthesis and classification of TPMs, that is it identifies the architectures that TPM legs must possess for the platform to be able to freely translate in space without altering its orientation. The second part studies both constraint and direct singularities of TPMs. In particular, special families of fully-isotropic mechanisms are identified. Such manipulators exhibit outstanding properties, as they are free from singularities and show a constant orthogonal Jacobian matrix throughout their workspace. As a consequence, both the direct and the inverse position problems are linear and the kinematic analysis proves straightforward.

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Neuronal circuits in the retina analyze images according to qualitative aspects such as color or motion, before the information is transmitted to higher visual areas of the brain. One example, studied for over the last four decades, is the detection of motion direction in ‘direction selective’ neurons. Recently, the starburst amacrine cell, one type of retinal interneuron, has emerged as an essential player in the computation of direction selectivity. In this study the mechanisms underlying the computation of direction selective calcium signals in starburst cell dendrites were investigated using whole-cell electrical recordings and two-photon calcium imaging. Analysis of the somatic electrical responses to visual stimulation and pharmacological agents indicated that the directional signal (i) is not computed presynaptically to starburst cells or by inhibitory network interactions. It is thus computed via a cell-intrinsic mechanism, which (ii) depends upon the differential, i.e. direction selective, activation of voltage-gated channels. Optically measuring dendritic calcium signals as a function of somatic voltage suggests (iii) a difference in resting membrane potential between the starburst cell’s soma and its distal dendrites. In conclusion, it is proposed that the mechanism underlying direction selectivity in starburst cell dendrites relies on intrinsic properties of the cell, particularly on the interaction of spatio-temporally structured synaptic inputs with voltage-gated channels, and their differential activation due to a somato-dendritic difference in membrane potential.

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Präsentiert wird ein vollständiger, exakter und effizienter Algorithmus zur Berechnung des Nachbarschaftsgraphen eines Arrangements von Quadriken (Algebraische Flächen vom Grad 2). Dies ist ein wichtiger Schritt auf dem Weg zur Berechnung des vollen 3D Arrangements. Dabei greifen wir auf eine bereits existierende Implementierung zur Berechnung der exakten Parametrisierung der Schnittkurve von zwei Quadriken zurück. Somit ist es möglich, die exakten Parameterwerte der Schnittpunkte zu bestimmen, diese entlang der Kurven zu sortieren und den Nachbarschaftsgraphen zu berechnen. Wir bezeichnen unsere Implementierung als vollständig, da sie auch die Behandlung aller Sonderfälle wie singulärer oder tangentialer Schnittpunkte einschließt. Sie ist exakt, da immer das mathematisch korrekte Ergebnis berechnet wird. Und schließlich bezeichnen wir unsere Implementierung als effizient, da sie im Vergleich mit dem einzigen bisher implementierten Ansatz gut abschneidet. Implementiert wurde unser Ansatz im Rahmen des Projektes EXACUS. Das zentrale Ziel von EXACUS ist es, einen Prototypen eines zuverlässigen und leistungsfähigen CAD Geometriekerns zu entwickeln. Obwohl wir das Design unserer Bibliothek als prototypisch bezeichnen, legen wir dennoch größten Wert auf Vollständigkeit, Exaktheit, Effizienz, Dokumentation und Wiederverwendbarkeit. Über den eigentlich Beitrag zu EXACUS hinaus, hatte der hier vorgestellte Ansatz durch seine besonderen Anforderungen auch wesentlichen Einfluss auf grundlegende Teile von EXACUS. Im Besonderen hat diese Arbeit zur generischen Unterstützung der Zahlentypen und der Verwendung modularer Methoden innerhalb von EXACUS beigetragen. Im Rahmen der derzeitigen Integration von EXACUS in CGAL wurden diese Teile bereits erfolgreich in ausgereifte CGAL Pakete weiterentwickelt.

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This work presents exact algorithms for the Resource Allocation and Cyclic Scheduling Problems (RA&CSPs). Cyclic Scheduling Problems arise in a number of application areas, such as in hoist scheduling, mass production, compiler design (implementing scheduling loops on parallel architectures), software pipelining, and in embedded system design. The RA&CS problem concerns time and resource assignment to a set of activities, to be indefinitely repeated, subject to precedence and resource capacity constraints. In this work we present two constraint programming frameworks facing two different types of cyclic problems. In first instance, we consider the disjunctive RA&CSP, where the allocation problem considers unary resources. Instances are described through the Synchronous Data-flow (SDF) Model of Computation. The key problem of finding a maximum-throughput allocation and scheduling of Synchronous Data-Flow graphs onto a multi-core architecture is NP-hard and has been traditionally solved by means of heuristic (incomplete) algorithms. We propose an exact (complete) algorithm for the computation of a maximum-throughput mapping of applications specified as SDFG onto multi-core architectures. Results show that the approach can handle realistic instances in terms of size and complexity. Next, we tackle the Cyclic Resource-Constrained Scheduling Problem (i.e. CRCSP). We propose a Constraint Programming approach based on modular arithmetic: in particular, we introduce a modular precedence constraint and a global cumulative constraint along with their filtering algorithms. Many traditional approaches to cyclic scheduling operate by fixing the period value and then solving a linear problem in a generate-and-test fashion. Conversely, our technique is based on a non-linear model and tackles the problem as a whole: the period value is inferred from the scheduling decisions. The proposed approaches have been tested on a number of non-trivial synthetic instances and on a set of realistic industrial instances achieving good results on practical size problem.

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A highly dangerous situations for tractor driver is the lateral rollover in operating conditions. Several accidents, involving tractor rollover, have indeed been encountered, requiring the design of a robust Roll-Over Protective Structure (ROPS). The aim of the thesis was to evaluate tractor behaviour in the rollover phase so as to calculate the energy absorbed by the ROPS to ensure driver safety. A Mathematical Model representing the behaviour of a generic tractor during a lateral rollover, with the possibility of modifying the geometry, the inertia of the tractor and the environmental boundary conditions, is proposed. The purpose is to define a method allowing the prediction of the elasto-plastic behaviour of the subsequent impacts occurring in the rollover phase. A tyre impact model capable of analysing the influence of the wheels on the energy to be absorbed by the ROPS has been also developed. Different tractor design parameters affecting the rollover behaviour, such as mass and dimensions, have been considered. This permitted the evaluation of their influence on the amount of energy to be absorbed by the ROPS. The mathematical model was designed and calibrated with respect to the results of actual lateral upset tests carried out on a narrow-track tractor. The dynamic behaviour of the tractor and the energy absorbed by the ROPS, obtained from the actual tests, showed to match the results of the model developed. The proposed approach represents a valuable tool in understanding the dynamics (kinetic energy) and kinematics (position, velocity, angular velocity, etc.) of the tractor in the phases of lateral rollover and the factors mainly affecting the event. The prediction of the amount of energy to be absorbed in some cases of accident is possible with good accuracy. It can then help in designing protective structures or active security devices.