Parallel hyperspectral unmixing method on GPU

Many Hyperspectral imagery applications require a response in real time or near-real time. To meet this requirement this paper proposes a parallel unmixing method developed for graphics processing units (GPU). This method is based on the vertex component analysis (VCA), which is a geometrical based method highly parallelizable. VCA is a very fast and accurate method that extracts endmember signatures from large hyperspectral datasets without the use of any a priori knowledge about the constituent spectra. Experimental results obtained for simulated and real hyperspectral datasets reveal considerable acceleration factors, up to 24 times.

Trends Of CPU, GPU and FPGA for high-performance computing

Floating-point computing with more than one TFLOP of peak performance is already a reality in recent Field-Programmable Gate Arrays (FPGA). General-Purpose Graphics Processing Units (GPGPU) and recent many-core CPUs have also taken advantage of the recent technological innovations in integrated circuit (IC) design and had also dramatically improved their peak performances. In this paper, we compare the trends of these computing architectures for high-performance computing and survey these platforms in the execution of algorithms belonging to different scientific application domains. Trends in peak performance, power consumption and sustained performances, for particular applications, show that FPGAs are increasing the gap to GPUs and many-core CPUs moving them away from high-performance computing with intensive floating-point calculations. FPGAs become competitive for custom floating-point or fixed-point representations, for smaller input sizes of certain algorithms, for combinational logic problems and parallel map-reduce problems. © 2014 Technical University of Munich (TUM).

GPU implementation of a hyperspectral coded aperture algorithm for compressive sensing

This paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA) algorithm for compressive sensing on graphics processing units (GPUs). HYCA method combines the ideas of spectral unmixing and compressive sensing exploiting the high spatial correlation that can be observed in the data and the generally low number of endmembers needed in order to explain the data. The proposed implementation exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs using shared memory and coalesced accesses to memory. The proposed algorithm is evaluated not only in terms of reconstruction error but also in terms of computational performance using two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN. Experimental results using real data reveals signficant speedups up with regards to serial implementation.

GPU implementation of the simplex identification via split augmented Lagrangian

Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Parallel hyperspectral compressive sensing method on GPU

Remote hyperspectral sensors collect large amounts of data per flight usually with low spatial resolution. It is known that the bandwidth connection between the satellite/airborne platform and the ground station is reduced, thus a compression onboard method is desirable to reduce the amount of data to be transmitted. This paper presents a parallel implementation of an compressive sensing method, called parallel hyperspectral coded aperture (P-HYCA), for graphics processing units (GPU) using the compute unified device architecture (CUDA). This method takes into account two main properties of hyperspectral dataset, namely the high correlation existing among the spectral bands and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. Experimental results conducted using synthetic and real hyperspectral datasets on two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN, reveal that the use of GPUs can provide real-time compressive sensing performance. The achieved speedup is up to 20 times when compared with the processing time of HYCA running on one core of the Intel i7-2600 CPU (3.4GHz), with 16 Gbyte memory.

Parallel hyperspectral coded aperture for compressive sensing on GPUs

The application of compressive sensing (CS) to hyperspectral images is an active area of research over the past few years, both in terms of the hardware and the signal processing algorithms. However, CS algorithms can be computationally very expensive due to the extremely large volumes of data collected by imaging spectrometers, a fact that compromises their use in applications under real-time constraints. This paper proposes four efficient implementations of hyperspectral coded aperture (HYCA) for CS, two of them termed P-HYCA and P-HYCA-FAST and two additional implementations for its constrained version (CHYCA), termed P-CHYCA and P-CHYCA-FAST on commodity graphics processing units (GPUs). HYCA algorithm exploits the high correlation existing among the spectral bands of the hyperspectral data sets and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. The proposed P-HYCA and P-CHYCA implementations have been developed using the compute unified device architecture (CUDA) and the cuFFT library. Moreover, this library has been replaced by a fast iterative method in the P-HYCA-FAST and P-CHYCA-FAST implementations that leads to very significant speedup factors in order to achieve real-time requirements. The proposed algorithms are evaluated not only in terms of reconstruction error for different compressions ratios but also in terms of computational performance using two different GPU architectures by NVIDIA: 1) GeForce GTX 590; and 2) GeForce GTX TITAN. Experiments are conducted using both simulated and real data revealing considerable acceleration factors and obtaining good results in the task of compressing remotely sensed hyperspectral data sets.

Vertex component analysis GPU-based implementation for hyperspectral unmixing

Endmember extraction (EE) is a fundamental and crucial task in hyperspectral unmixing. Among other methods vertex component analysis ( VCA) has become a very popular and useful tool to unmix hyperspectral data. VCA is a geometrical based method that extracts endmember signatures from large hyperspectral datasets without the use of any a priori knowledge about the constituent spectra. Many Hyperspectral imagery applications require a response in real time or near-real time. Thus, to met this requirement this paper proposes a parallel implementation of VCA developed for graphics processing units. The impact on the complexity and on the accuracy of the proposed parallel implementation of VCA is examined using both simulated and real hyperspectral datasets.

Parallel hyperspectral unmixing method via split augmented lagrangian on GPU

One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.

Solid-state Marx based two-switch voltage modulator for the On-Line Isotope Mass Separator accelerator at the European Organization for Nuclear Research

A new circuit topology is proposed to replace the actual pulse transformer and thyratron based resonant modulator that supplies the 60 kV target potential for the ion acceleration of the On-Line Isotope Mass Separator accelerator, the stability of which is critical for the mass resolution downstream separator, at the European Organization for Nuclear Research. The improved modulator uses two solid-state switches working together, each one based on the Marx generator concept, operating as series and parallel switches, reducing the stress on the series stacked semiconductors, and also as auxiliary pulse generator in order to fulfill the target requirements. Preliminary results of a 10 kV prototype, using 1200 V insulated gate bipolar transistors and capacitors in the solid-state Marx circuits, ten stages each, with an electrical equivalent circuit of the target, are presented, demonstrating both the improved voltage stability and pulse flexibility potential wanted for this new modulator.

Rearranjos 3-aza-cope de N-alil-N-sililoxi enaminas

O rearranjo [3,3]-sigmatrópico térmico (180ºC) de diferentes N-alil-N-sililoxi enaminas foi estudado. Os respectivos produtos de rearranjo (éteres de óxima) foram obtidos com rendimentos elevados (80%). A regiosselectividade, [3,3] vs [1,3], e a diastereosselectividade do processo foram elevadas, superior a 99% e aproximadamente 80%, respectivamente. Foi demonstrada a importância do grupo sililoxilo na promoção do rearranjo face a substratos sem este tipo de substituição. Posteriormente, foi estudada a possibilidade de aceleração aniónica deste tipo de rearranjo por formação de oxianião ligado ao átomo de azoto. A estratégia seguida para a formação do mesmo, consistiu na O-dessililação de diferentes N-alil-N-sililoxi enaminas tendo-se obtido as nitronas correspondentes ou produtos de ciclização. Num exemplo envolvendo um derivado de isoxazole-5-(2H)-ona foi observado um aumento de velocidade do rearranjo por reacção com ião etoxilo. Este aumento de velocidade foi atribuído à abertura de anel do N-O éster cíclico para o N-oxianião, seguida de rearranjo e posterior fecho. Métodos alternativos de aceleração do rearranjo por geração de carga positiva, parcial ou completa, no átomo de azoto levaram apenas à dessililação das N-alil-N-sililoxi enaminas. ABSTRACT - [3,3]-sigmatropic rearrangement of a variety of N-allyl-N-silyloxy enamines was studied. The corresponding rearrangement products (oxime-ethers) were obtained in high yields (80%). High regioselectivity, [3,3] vs [1,3] (> 99%) and in appropriate cases, diastereoselectivity (80%) were observed. The importance of the silyloxy group in promoting the rearrangement, in relation to substrates lacking this functionality, is underlined. The possible anionic acceleration of the rearrangements was next examined by O-desilylation the N-silyloxy group bonded to the nitrogen. Attempted generation of these species however, was found to lead either to the corresponding nitrones or to cyclization products. In one particular example involving an isoxazol-5-(2H)-one derivative rate enhancement of rearrangement was indeed observed with ethoxide ion. It is tentatively attributed to ring opening of the cyclic N-O ester to the N-oxyanion ethyl ester followed by rearrangement and subsequent reclosure. Alternative methods to accelerate the process by generating a partial or complete positive charge on the nitrogen atom led only to desilylation.

Analisador de vibrações de dois canais baseado em computador

O presente trabalho teve como principal objectivo o desenvolvimento de um analisador de vibrações de dois canais baseado em computador, para a realização de diagnóstico no âmbito do controlo de condição de máquinas. Foi desenvolvida uma aplicação num computador comum, no software LabVIEW, que através de transdutores de aceleração do tipo MEMS conectados via USB, faz a recolha de dados de vibração e procede ao seu processamento e apresentação ao utilizador. As ferramentas utilizadas para o processamento de dados são ferramentas comuns encontradas em vários analisadores de vibrações disponíveis no mercado. Estas podem ser: gráficos de espectro de frequência, sinal no tempo, cascata ou valores de nível global de vibração, entre outras. Apesar do analisador desenvolvido não apresentar inovação nas ferramentas de análise adoptadas, este pretende ser distinguido pelo baixo custo, simplicidade e carácter didáctico. Este trabalho vem evidenciar as vantagens, desvantagens e potencialidades de um analisador desta natureza. São tiradas algumas conclusões quanto à sua capacidade de diagnóstico de avarias, capacidades como ferramenta didáctica, sensores utilizados e linguagem de programação escolhida. Como conclusões principais, o trabalho revela que os sensores escolhidos não são os indicados para efectuar o diagnóstico de avarias em ambiente industrial, contudo são ideais para tornar este analisador numa boa ferramenta didáctica e de treino.

Desenvolvimento do sistema de tracção de um veículo eléctrico ecológico com travagem regenerativa

Nesta dissertação descreve-se uma metodologia de dimensionamento do sistema de tracção para equipar um veículo eléctrico ecológico (VEECO) com inclusão de um sistema de travagem regenerativa. Apresenta-se uma perspectiva geral de diversas topologias de sistemas de tracção utilizadas nos veículos eléctricos e realiza-se a sua comparação através do estudo e análise dos acionamentos electromecânicos que podem ser utilizados nesses sistemas de tracção eléctrica. Utilizando ferramentas de simulação numérica, estuda-se o modelo matemático de um veículo eléctrico com travagem regenerativa. A partir deste modelo matemático é adoptado uma possível configuração para o seu sistema de tracção eléctrica e são obtidas características teóricas de desempenho do veículo eléctrico, através da análise de testes padrão ao veículo. Em banco de ensaios, constrói-se um sistema de tracção eléctrica que permite a validação experimental do modelo matemático do veículo eléctrico. Para a construção deste banco de ensaios foram concebidos os sistemas de tracção eléctrica, de carga mecânica e de controlo e monitorização do banco de ensaios. A validação experimental realiza-se através dos mesmos testes padrão ao veículo eléctrico, como o teste NEDC (New European Driving Cycle), o teste de aceleração entre 0 e 100km/h e o teste de gradeabilidade. Desenvolve-se o dimensionamento do sistema de tracção eléctrica a equipar o VEECO, através da componente de modelação paramétrica do modelo matemático do veículo eléctrico. Com esta metodologia é adoptado um conjunto de variáveis paramétricas relacionadas com os elementos que constituem o sistema de tracção eléctrica do VEECO. Estuda-se a influência destas variáveis paramétricas nas características de desempenho pretendidas para o VEECO. Como resultado da análise de modelação paramétrica é apresentada uma solução para o sistema de tracção eléctrica do VEECO que cumpre a execução do NEDC, apresenta um tempo de aceleração entre 0 e 100km/h inferior a 10 segundos, supera uma gradeabilidade de 10% e uma autonomia de 200 km. O sistema de tracção do VEECO também permite realizar a travagem regenerativa com rendimento até 33%. Possui controlo de tracção e anti bloqueio da roda motora, através de uma unidade de controlo que permite reduzir a potência transmitida ao veio, quando a velocidade da roda de tracção difere do valor de referência da velocidade do veículo. Os conhecimentos adquiridos através do processo de investigação e desenvolvimento, para a realização da presente dissertação permitem apresentar perspectivas de desenvolvimento futuro com aplicação nos sistemas de tracção de veículos eléctricos rodoviários.

Surge damping analysis in pipe systems: modelling and experiments

The current study focuses on the analysis of pressure surge damping in single pipeline systems generated by a fast change of flow, conditions. A dimensionless form of pressurised transient flow equations was developed. presenting the main advantage of being independent of the system characteristics. In lack of flow velocity profiles. the unsteady friction in turbulent regimes is analysed based on two new empirical corrective-coefficients associated with local and convective acceleration terms. A new, surge damping approach is also presented taking into account the pressure peak time variation. The observed attenuation effect in the pressure wave for high deformable pipe materials can be described by a combination of the non-elastic behaviour of the pipe-wall with steady and unsteady friction effects. Several simulations and experimental tests have been carried out. in order to analyse the dynamic response of single pipelines with different characteristics, such as pipe materials. diameters. thickness. lengths and transient conditions.

Angular and linear accelerations of a rolling cylinder acted by an external force

The dynamics of a cylinder rolling on a horizontal plane acted on by an external force applied at an arbitrary angle is studied with emphasis on the directions of the acceleration of the centre-of-mass and the angular acceleration of the body. If rolling occurs without slipping, there is a relationship between the directions of these accelerations. If the linear acceleration points to the right, then the angular acceleration is clockwise. On the other hand, if it points to the left, then the angular acceleration is counterclockwise. In contrast, if rolling and slipping occurs, the direction of the linear acceleration does not determine the direction of the angular acceleration. For example, the linear acceleration may point to the right and the angular acceleration clockwise or counterclockwise depending on the external force orientation and point of application.