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.

Parallel sparse unmixing of hyperspectral data

In this paper, a new parallel method for sparse spectral unmixing of remotely sensed hyperspectral data on commodity graphics processing units (GPUs) is presented. A semi-supervised approach is adopted, which relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. This method is based on the spectral unmixing by splitting and augmented Lagrangian (SUNSAL) that estimates the material's abundance fractions. The parallel method is performed in a pixel-by-pixel fashion and its implementation properly exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for simulated and real hyperspectral datasets reveal significant speedup factors, up to 1 64 times, with regards to optimized serial implementation.

Anaerobic bio-digestion of concentrate obtained in the process of ultra filtration of effluents from tilapia processing unit

The objective of the present study was to evaluate the efficiency of the process of biodigestion of the protein concentrate resulting from the ultrafiltration of the effluent from a slaughterhouse freezer of Nile tilapia. Bench digesters were used with excrements and water (control) in comparison with a mixture of cattle manure and effluent from the stages of filleting and bleeding of tilapias. The effluent obtained in the continuous process (bleeding + filleting) was the one with highest accumulated population from the 37th day, as well as greatest daily production. Gases composition did not differ between the protein concentrates, but the gas obtained with the use of the effluent from the filleting stage presented highest methane gas average (78.05%) in comparison with those obtained in the bleeding stage (69.95%) and in the continuous process (70.02%) or by the control method (68.59%).

Nucleation studies on graphics processing units

Ein System in einem metastabilen Zustand muss eine bestimmte Barriere in derrnfreien Energie überwinden um einen Tropfen der stabilen Phase zu formen.rnHerkömmliche Untersuchungen nehmen hierbei kugelförmige Tropfen an. Inrnanisotropen Systemen (wie z.B. Kristallen) ist diese Annahme aber nicht ange-rnbracht. Bei tiefen Temperaturen wirkt sich die Anisotropie des Systems starkrnauf die freie Energie ihrer Oberfläche aus. Diese Wirkung wird oberhalb derrnAufrauungstemperatur T R schwächer. Das Ising-Modell ist ein einfaches Mo-rndell, welches eine solche Anisotropie aufweist. Wir führen großangelegte Sim-rnulationen durch, um die Effekte, die mit einer endlichen Simulationsbox ein-rnhergehen, sowie statistische Ungenauigkeiten möglichst klein zu halten. DasrnAusmaß der Simulationen die benötigt werden um sinnvolle Ergebnisse zu pro-rnduzieren, erfordert die Entwicklung eines skalierbaren Simulationsprogrammsrnfür das Ising-Modell, welcher auf verschiedenen parallelen Architekturen (z.B.rnGrafikkarten) verwendet werden kann. Plattformunabhängigkeit wird durch ab-rnstrakte Schnittstellen erreicht, welche plattformspezifische Implementierungs-rndetails verstecken. Wir benutzen eine Systemgeometrie die es erlaubt eine Ober-rnfläche mit einem variablen Winkel zur Kristallebene zu untersuchen. Die Ober-rnfläche ist in Kontakt mit einer harten Wand, wobei der Kontaktwinkel Θ durchrnein Oberflächenfeld eingestellt werden kann. Wir leiten eine Differenzialglei-rnchung ab, welche das Verhalten der freien Energie der Oberfläche in einemrnanisotropen System beschreibt. Kombiniert mit thermodynamischer Integrationrnkann die Gleichung benutzt werden, um die anisotrope Oberflächenspannungrnüber einen großen Winkelbereich zu integrieren. Vergleiche mit früheren Mes-rnsungen in anderen Geometrien und anderen Methoden zeigen hohe Überein-rnstimung und Genauigkeit, welche vor allem durch die im Vergleich zu früherenrnMessungen wesentlich größeren Simulationsdomänen erreicht wird. Die Temper-rnaturabhängigkeit der Oberflächensteifheit κ wird oberhalb von T R durch diernKrümmung der freien Energie der Oberfläche für kleine Winkel gemessen. DiesernMessung lässt sich mit Simulationsergebnissen in der Literatur vergleichen undrnhat bessere Übereinstimmung mit theoretischen Voraussagen über das Skalen-rnverhalten von κ. Darüber hinaus entwickeln wir ein Tieftemperatur-Modell fürrndas Verhalten um Θ = 90 Grad weit unterhalb von T R. Der Winkel bleibt bis zu einemrnkritischen Feld H C quasi null; oberhalb des kritischen Feldes steigt der Winkelrnrapide an. H C wird mit der freien Energie einer Stufe in Verbindung gebracht,rnwas es ermöglicht, das kritische Verhalten dieser Größe zu analysieren. Die harternWand muss in die Analyse einbezogen werden. Durch den Vergleich freier En-rnergien bei geschickt gewählten Systemgrößen ist es möglich, den Beitrag derrnKontaktlinie zur freien Energie in Abhängigkeit von Θ zu messen. Diese Anal-rnyse wird bei verschiedenen Temperaturen durchgeführt. Im letzten Kapitel wirdrneine 2D Fluiddynamik Simulation für Grafikkarten parallelisiert, welche u. a.rnbenutzt werden kann um die Dynamik der Atmosphäre zu simulieren. Wir im-rnplementieren einen parallelen Evolution Galerkin Operator und erreichen

GPU-based Ray Tracing of Dynamic Scenes

Interactive ray tracing of non-trivial scenes is just becoming feasible on single graphics processing units (GPU). Recent work in this area focuses on building effective acceleration structures, which work well under the constraints of current GPUs. Most approaches are targeted at static scenes and only allow navigation in the virtual scene. So far support for dynamic scenes has not been considered for GPU implementations. We have developed a GPU-based ray tracing system for dynamic scenes consisting of a set of individual objects. Each object may independently move around, but its geometry and topology are static.

Neural Processing Unit based on the Optical Bistable Properties of Semiconductor Laser Amplifiers

This paper analyzes the behavior of a neural processing unit based on the optical bistable properties of semiconductor laser amplifiers. A similar unit to the reported here was previously employed in the simulation of the mammalian retina. The main advantages of the present cell are its larger fan-out and the possibility of different responses according to the light wavelength impinging onto the cell. These properties allow to work with larger structures as well as to obtain different behaviors according to the light characteristics. This new approach gives a possible modeling closer to the real biological configurations. Moreover, a more detailed analysis of the basic cell internal behavior is reported

Operator's manual : processing equipment PH-406 and photographic film processing unit ES-20(1).

"May 1958."

Organizational and direct support maintenance manual : data processing unit CP-1435/MYQ-4, (NSN 7010-01-092-2549).

Includes index.

Strategies for protecting intellectual property when using CUDA applications on graphics processing units

Recent advances in the massively parallel computational abilities of graphical processing units (GPUs) have increased their use for general purpose computation, as companies look to take advantage of big data processing techniques. This has given rise to the potential for malicious software targeting GPUs, which is of interest to forensic investigators examining the operation of software. The ability to carry out reverse-engineering of software is of great importance within the security and forensics elds, particularly when investigating malicious software or carrying out forensic analysis following a successful security breach. Due to the complexity of the Nvidia CUDA (Compute Uni ed Device Architecture) framework, it is not clear how best to approach the reverse engineering of a piece of CUDA software. We carry out a review of the di erent binary output formats which may be encountered from the CUDA compiler, and their implications on reverse engineering. We then demonstrate the process of carrying out disassembly of an example CUDA application, to establish the various techniques available to forensic investigators carrying out black-box disassembly and reverse engineering of CUDA binaries. We show that the Nvidia compiler, using default settings, leaks useful information. Finally, we demonstrate techniques to better protect intellectual property in CUDA algorithm implementations from reverse engineering.

Anaerobic bio-digestion of concentrate obtained in the process of ultra filtration of effluents from tilapia processing unit

The objective of the present study was to evaluate the efficiency of the process of biodigestion of the protein concentrate resulting from the ultrafiltration of the effluent from a slaughterhouse freezer of Nile tilapia. Bench digesters were used with excrements and water (control) in comparison with a mixture of cattle manure and effluent from the stages of filleting and bleeding of tilapias. The effluent obtained in the continuous process (bleeding + filleting) was the one with highest accumulated population from the 37th day, as well as greatest daily production. Gases composition did not differ between the protein concentrates, but the gas obtained with the use of the effluent from the filleting stage presented highest methane gas average (78.05%) in comparison with those obtained in the bleeding stage (69.95%) and in the continuous process (70.02%) or by the control method (68.59%).

Parallel implementation of vertex component analysis for hyperspectral endmember extraction

International Conference with Peer Review 2012 IEEE International Conference in Geoscience and Remote Sensing Symposium (IGARSS), 22-27 July 2012, Munich, Germany

Econometrics on GPUs

A graphical processing unit (GPU) is a hardware device normally used to manipulate computer memory for the display of images. GPU computing is the practice of using a GPU device for scientific or general purpose computations that are not necessarily related to the display of images. Many problems in econometrics have a structure that allows for successful use of GPU computing. We explore two examples. The first is simple: repeated evaluation of a likelihood function at different parameter values. The second is a more complicated estimator that involves simulation and nonparametric fitting. We find speedups from 1.5 up to 55.4 times, compared to computations done on a single CPU core. These speedups can be obtained with very little expense, energy consumption, and time dedicated to system maintenance, compared to equivalent performance solutions using CPUs. Code for the examples is provided.

Técnicas de paralelização em GPGPU aplicadas em algoritmo para remoção de ruído multiplicativo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Image Re-Ranking Acceleration on GPUs

Huge image collections are becoming available lately. In this scenario, the use of Content-Based Image Retrieval (CBIR) systems has emerged as a promising approach to support image searches. The objective of CBIR systems is to retrieve the most similar images in a collection, given a query image, by taking into account image visual properties such as texture, color, and shape. In these systems, the effectiveness of the retrieval process depends heavily on the accuracy of ranking approaches. Recently, re-ranking approaches have been proposed to improve the effectiveness of CBIR systems by taking into account the relationships among images. The re-ranking approaches consider the relationships among all images in a given dataset. These approaches typically demands a huge amount of computational power, which hampers its use in practical situations. On the other hand, these methods can be massively parallelized. In this paper, we propose to speedup the computation of the RL-Sim algorithm, a recently proposed image re-ranking approach, by using the computational power of Graphics Processing Units (GPU). GPUs are emerging as relatively inexpensive parallel processors that are becoming available on a wide range of computer systems. We address the image re-ranking performance challenges by proposing a parallel solution designed to fit the computational model of GPUs. We conducted an experimental evaluation considering different implementations and devices. Experimental results demonstrate that significant performance gains can be obtained. Our approach achieves speedups of 7x from serial implementation considering the overall algorithm and up to 36x on its core steps.

Implementação do algoritmo de Newman para identificação de comunidades em placas gráficas

Communities are present on physical, chemical and biological systems and their identification is fundamental for the comprehension of the behavior of these systems. Recently, available data related to complex networks have grown exponentially, demanding more computational power. The Graphical Processing Unit (GPU) is a cost effective alternative suitable for this purpose. We investigate the convenience of this for network science by proposing a GPU based implementation of Newman community detection algorithm. We showed that the processing time of matrix multiplications of GPUs grow slower than CPUs in relation to the matrix size. It was proven, thus, that GPU processing power is a viable solution for community dentification simulation that demand high computational power. Our implementation was tested on an integrated biological network for the bacterium Escherichia coli