847 resultados para Graphics Processor Unit


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This paper presents a non-rigid free-from 2D-3D registration approach using statistical deformation model (SDM). In our approach the SDM is first constructed from a set of training data using a non-rigid registration algorithm based on b-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D-3D registration algorithm is then presented to iteratively fit the 3D b-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Experiments conducted on C-arm and X-ray images of cadaveric femurs demonstrate the efficacy of the present approach.

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In the present article, an innovative approach for generation of an UWB monocycle is proposed and experimentally demonstrated. The proposed design features the combination of an interferometric device (SOA-Mach Zehnder interferometer) with an optical processor unit. The fusion of such components permits to generate, combine and customize UWB pulses. An optical pulse is used as pump signal and two optical carriers represent and the optical input of the system. The selection of a specific wavelength and therefore of a particular port provides the possibility of modifying the systems output pulse polarity. The capacity of transmitting several data sequence has been also evidenced.

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The last generation of consumer electronic devices is endowed with Augmented Reality (AR) tools. These tools require moving object detection strategies, which should be fast and efficient, to carry out higher level object analysis tasks. We propose a lightweight spatio-temporal-based non-parametric background-foreground modeling strategy in a General Purpose Graphics Processing Unit (GPGPU), which provides real-time high-quality results in a great variety of scenarios and is suitable for AR applications.

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El objetivo de este proyecto es evaluar la mejora de rendimiento que aporta la paralelización de algoritmos de procesamiento de imágenes, para su ejecución en una tarjeta gráfica. Para ello, una vez seleccionados los algoritmos a estudio, fueron desarrollados en lenguaje C++ bajo el paradigma secuencial. A continuación, tomando como base estas implementaciones, se paralelizaron siguiendo las directivas de la tecnología CUDA (Compute Unified Device Architecture) desarrollada por NVIDIA. Posteriormente, se desarrolló un interfaz gráfico de usuario en Visual C#, para una utilización más sencilla de la herramienta. Por último, se midió el rendimiento de cada uno de los algoritmos, en términos de tiempo de ejecución paralela y speedup, mediante el procesamiento de una serie de imágenes de distintos tamaños.---ABSTRACT---The aim of this Project is to evaluate the performance improvement provided by the parallelization of image processing algorithms, which will be executed on a graphics processing unit. In order to do this, once the algorithms to study were selected, each of them was developed in C++ under sequential paradigm. Then, based on these implementations, these algorithms were implemented using the compute unified device architecture (CUDA) programming model provided by NVIDIA. After that, a graphical user interface (GUI) was developed to increase application’s usability. Finally, performance of each algorithm was measured in terms of parallel execution time and speedup by processing a set of images of different sizes.

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Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

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The focus of this study is development of parallelised version of severely sequential and iterative numerical algorithms based on multi-threaded parallel platform such as a graphics processing unit. This requires design and development of a platform-specific numerical solution that can benefit from the parallel capabilities of the chosen platform. Graphics processing unit was chosen as a parallel platform for design and development of a numerical solution for a specific physical model in non-linear optics. This problem appears in describing ultra-short pulse propagation in bulk transparent media that has recently been subject to several theoretical and numerical studies. The mathematical model describing this phenomenon is a challenging and complex problem and its numerical modeling limited on current modern workstations. Numerical modeling of this problem requires a parallelisation of an essentially serial algorithms and elimination of numerical bottlenecks. The main challenge to overcome is parallelisation of the globally non-local mathematical model. This thesis presents a numerical solution for elimination of numerical bottleneck associated with the non-local nature of the mathematical model. The accuracy and performance of the parallel code is identified by back-to-back testing with a similar serial version.

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This thesis describes advances in the characterisation, calibration and data processing of optical coherence tomography (OCT) systems. Femtosecond (fs) laser inscription was used for producing OCT-phantoms. Transparent materials are generally inert to infra-red radiations, but with fs lasers material modification occurs via non-linear processes when the highly focused light source interacts with the materials. This modification is confined to the focal volume and is highly reproducible. In order to select the best inscription parameters, combination of different inscription parameters were tested, using three fs laser systems, with different operating properties, on a variety of materials. This facilitated the understanding of the key characteristics of the produced structures with the aim of producing viable OCT-phantoms. Finally, OCT-phantoms were successfully designed and fabricated in fused silica. The use of these phantoms to characterise many properties (resolution, distortion, sensitivity decay, scan linearity) of an OCT system was demonstrated. Quantitative methods were developed to support the characterisation of an OCT system collecting images from phantoms and also to improve the quality of the OCT images. Characterisation methods include the measurement of the spatially variant resolution (point spread function (PSF) and modulation transfer function (MTF)), sensitivity and distortion. Processing of OCT data is a computer intensive process. Standard central processing unit (CPU) based processing might take several minutes to a few hours to process acquired data, thus data processing is a significant bottleneck. An alternative choice is to use expensive hardware-based processing such as field programmable gate arrays (FPGAs). However, recently graphics processing unit (GPU) based data processing methods have been developed to minimize this data processing and rendering time. These processing techniques include standard-processing methods which includes a set of algorithms to process the raw data (interference) obtained by the detector and generate A-scans. The work presented here describes accelerated data processing and post processing techniques for OCT systems. The GPU based processing developed, during the PhD, was later implemented into a custom built Fourier domain optical coherence tomography (FD-OCT) system. This system currently processes and renders data in real time. Processing throughput of this system is currently limited by the camera capture rate. OCTphantoms have been heavily used for the qualitative characterization and adjustment/ fine tuning of the operating conditions of OCT system. Currently, investigations are under way to characterize OCT systems using our phantoms. The work presented in this thesis demonstrate several novel techniques of fabricating OCT-phantoms and accelerating OCT data processing using GPUs. In the process of developing phantoms and quantitative methods, a thorough understanding and practical knowledge of OCT and fs laser processing systems was developed. This understanding leads to several novel pieces of research that are not only relevant to OCT but have broader importance. For example, extensive understanding of the properties of fs inscribed structures will be useful in other photonic application such as making of phase mask, wave guides and microfluidic channels. Acceleration of data processing with GPUs is also useful in other fields.

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Femtosecond laser microfabrication has emerged over the last decade as a 3D flexible technology in photonics. Numerical simulations provide an important insight into spatial and temporal beam and pulse shaping during the course of extremely intricate nonlinear propagation (see e.g. [1,2]). Electromagnetics of such propagation is typically described in the form of the generalized Non-Linear Schrdinger Equation (NLSE) coupled with Drude model for plasma [3]. In this paper we consider a multi-threaded parallel numerical solution for a specific model which describes femtosecond laser pulse propagation in transparent media [4, 5]. However our approach can be extended to similar models. The numerical code is implemented in NVIDIA Graphics Processing Unit (GPU) which provides an effitient hardware platform for multi-threded computing. We compare the performance of the described below parallel code implementated for GPU using CUDA programming interface [3] with a serial CPU version used in our previous papers [4,5]. © 2011 IEEE.

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We describe a parallel multi-threaded approach for high performance modelling of wide class of phenomena in ultrafast nonlinear optics. Specific implementation has been performed using the highly parallel capabilities of a programmable graphics processor. © 2011 SPIE.

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INTRODUCTION The Rondo is a single-unit cochlear implant (CI) audio processor comprising the identical components as its behind-the-ear predecessor, the Opus 2. An interchange of the Opus 2 with the Rondo leads to a shift of the microphone position toward the back of the head. This study aimed to investigate the influence of the Rondo wearing position on speech intelligibility in noise. METHODS Speech intelligibility in noise was measured in 4 spatial configurations with 12 experienced CI users using the German adaptive Oldenburg sentence test. A physical model and a numerical model were used to enable a comparison of the observations. RESULTS No statistically significant differences of the speech intelligibility were found in the situations in which the signal came from the front and the noise came from the frontal, ipsilateral, or contralateral side. The signal-to-noise ratio (SNR) was significantly better with the Opus 2 in the case with the noise presented from the back (4.4 dB, p < 0.001). The differences in the SNR were significantly worse with the Rondo processors placed further behind the ear than closer to the ear. CONCLUSION The study indicates that CI users with the receiver/stimulator implanted in positions further behind the ear are expected to have higher difficulties in noisy situations when wearing the single-unit audio processor.

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The Intel R Xeon PhiTM is the first processor based on Intel’s MIC (Many Integrated Cores) architecture. It is a co-processor specially tailored for data-parallel computations, whose basic architectural design is similar to the ones of GPUs (Graphics Processing Units), leveraging the use of many integrated low computational cores to perform parallel computations. The main novelty of the MIC architecture, relatively to GPUs, is its compatibility with the Intel x86 architecture. This enables the use of many of the tools commonly available for the parallel programming of x86-based architectures, which may lead to a smaller learning curve. However, programming the Xeon Phi still entails aspects intrinsic to accelerator-based computing, in general, and to the MIC architecture, in particular. In this thesis we advocate the use of algorithmic skeletons for programming the Xeon Phi. Algorithmic skeletons abstract the complexity inherent to parallel programming, hiding details such as resource management, parallel decomposition, inter-execution flow communication, thus removing these concerns from the programmer’s mind. In this context, the goal of the thesis is to lay the foundations for the development of a simple but powerful and efficient skeleton framework for the programming of the Xeon Phi processor. For this purpose we build upon Marrow, an existing framework for the orchestration of OpenCLTM computations in multi-GPU and CPU environments. We extend Marrow to execute both OpenCL and C++ parallel computations on the Xeon Phi. We evaluate the newly developed framework, several well-known benchmarks, like Saxpy and N-Body, will be used to compare, not only its performance to the existing framework when executing on the co-processor, but also to assess the performance on the Xeon Phi versus a multi-GPU environment.

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Most of the commercial and financial data are stored in decimal fonn. Recently, support for decimal arithmetic has received increased attention due to the growing importance in financial analysis, banking, tax calculation, currency conversion, insurance, telephone billing and accounting. Performing decimal arithmetic with systems that do not support decimal computations may give a result with representation error, conversion error, and/or rounding error. In this world of precision, such errors are no more tolerable. The errors can be eliminated and better accuracy can be achieved if decimal computations are done using Decimal Floating Point (DFP) units. But the floating-point arithmetic units in today's general-purpose microprocessors are based on the binary number system, and the decimal computations are done using binary arithmetic. Only few common decimal numbers can be exactly represented in Binary Floating Point (BF P). ln many; cases, the law requires that results generated from financial calculations performed on a computer should exactly match with manual calculations. Currently many applications involving fractional decimal data perform decimal computations either in software or with a combination of software and hardware. The performance can be dramatically improved by complete hardware DFP units and this leads to the design of processors that include DF P hardware.VLSI implementations using same modular building blocks can decrease system design and manufacturing cost. A multiplexer realization is a natural choice from the viewpoint of cost and speed.This thesis focuses on the design and synthesis of efficient decimal MAC (Multiply ACeumulate) architecture for high speed decimal processors based on IEEE Standard for Floating-point Arithmetic (IEEE 754-2008). The research goal is to design and synthesize deeimal'MAC architectures to achieve higher performance.Efficient design methods and architectures are developed for a high performance DFP MAC unit as part of this research.

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El presente proyecto tiene como objeto caracterizar y optimizar un equipo de sonido profesional, entendiendo por “caracterizar” el determinar los atributos particulares de cada uno de los componentes integrados en el sistema, y entendiendo por “optimizar” el hallar la mejor manera de obtener una respuesta plana para todo el rango de frecuencias, libre de distorsión, y en la mayor área posible. El sistema de sonido utilizado pertenece a un grupo musical de directo, por lo que se instala y se configura en cada concierto en función de las características del recinto, sea cerrado o al aire libre. Con independencia de estas particularidades, el sistema completo se divide en dos formaciones, L y R (lado izquierdo y lado derecho del escenario), por lo que cada formación se compone de un procesador digital de la señal, cuatro etapas de amplificación, un sistema line array de ocho unidades, y un conjunto de ocho altavoces de subgraves. Para llevar a cabo el objetivo planteado, se ha dividido el proyecto en las fases que a continuación se describen. En primer lugar, se han realizado, en la cámara anecoica de la EUITT, las medidas que permiten obtener las características de cada uno de los elementos que componen el sistema. Estas medidas se han almacenado en formato ASCII. En segundo lugar, se ha diseñado una interfaz gráfica que permite, utilizando las medidas almacenadas, caracterizar tanto la respuesta individual de cada elemento de la cadena del sistema de sonido como la respuesta combinada de una unidad line array y una unidad de subgraves. La interfaz es interactiva, y tiene además la capacidad de entregar automáticamente los valores de configuración que permiten la optimización del conjunto. Esto es, obtener alineamiento en el rango de frecuencias compartido por ambas unidades. Las medidas realizadas en la cámara anecoica se han utilizado igualmente para modelar el sistema line array al completo y poder realizar simulaciones en campo libre utilizando programas de predicción acústica. Se ha experimentado con los valores de configuración que permiten el alineamiento de los elementos individuales y obtenidos a través de la interfaz desarrollada, para comprobar la validez de los mismos con la formación line array y subgraves al completo. Por otro lado, se han analizado los métodos de optimización de sistemas propuestos por profesionales reconocidos del medio con el objetivo de aplicarlos en un evento real. En la preparación y montaje del evento, se han aplicado los valores de configuración proporcionados por la interfaz, y se ha comprobado la validez de los mismos realizando medidas in situ según los criterios propuestos en los métodos de optimización estudiados. ABSTRACT. This project aims to characterize and optimize a professional sound system. Characterize must be understood as determining the particular attributes of each component integrated in the system; optimize must be understood as finding the best way to get a flat response for all the frequency range, distortion free, in the largest possible area. The sound system under test belongs to a live musical group, so it is setup and configured on each concert depending on the characteristics of the enclosure, whether it’s indoor or outdoor. Apart from these features, the whole system is divided into two clusters, L and R (left and right side of the stage), so that each one is provided with a digital signal processor, four amplification stages, an eight-units line array system, and a set of eight subwoofers . To accomplish the stated objective, the project has been divided into the steps described below. To begin with, measures have been realized in the anechoic chamber of EUITT, which make possible obtaining the characteristics of each of the elements of the system. These measures have been stored in ASCII format. Then, a graphical interface has been designed that allow, using the stored measurements and from graphics, to characterize both the individual response of each element of the string sound system and the combined response of the several elements. The interface is interactive, and also has the ability to automatically deliver the configuration settings that allow the whole optimization. That means to get alignment in the frequency range shared by a line array unit and a subwoofer unit. The measurements made in the anechoic chamber have also been used to model the complete line array system and to perform free-field simulations using acoustical prediction programs. Simulations have been done with the configuration settings that allow the individual elements alignment (provided by the graphical interface developed), in order to check their validity with the full line array and subwoofer systems. On the other hand, analysis about the optimization methods, proposed by renowned professionals of the field, has been made in order to apply them in a real concert. In the setup and assembly of the event, configuration settings provided by the interface have been applied. Their validity has been proved by making measures on-site according to the criteria set in the studied optimization methods.

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This paper presents an approach to create what we have called a Unified Sentiment Lexicon (USL). This approach aims at aligning, unifying, and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. One problem related to the task of the automatic unification of different scores of sentiment lexicons is that there are multiple lexical entries for which the classification of positive, negative, or neutral {P, Z, N} depends on the unit of measurement used in the annotation methodology of the source sentiment lexicon. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and -1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and so is the UnifiedMetrics procedure for CPU and GPU, respectively. Another problem is the high processing time required for computing all the lexical entries in the unification task. Thus, the USL approach computes a subset of lexical entries in each of the 1344 GPU cores and uses parallel processing in order to unify 155802 lexical entries. The results of the analysis conducted using the USL approach show that the USL has 95.430 lexical entries, out of which there are 35.201 considered to be positive, 22.029 negative, and 38.200 neutral. Finally, the runtime was 10 minutes for 95.430 lexical entries; this allows a reduction of the time computing for the UnifiedMetrics by 3 times.

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Photocopy of typescript.