Heterogeneous multicore systems for signal processing

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.

Parallel programming in biomedical signal processing

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

A Feasibility Study of a Pelleting Plant as an Option for By Product Upgrading in Wood-Processing Industry

Tämän kannattavuustutkimuksen lähtökohtana oli se, että Yhtyneet Sahat Oy:n Kaukaan sahalla ja Luumäen jatkojalostuslaitoksella haluttiin selvittää pellettitehtaan kannattavuus nykyisessä markkinatilanteessa. Tämä työon luonteeltaan teknis-taloudellinen selvitys eli ns. feasibility study. Pelletöintiprosessi on tekniikaltaan yksinkertainen eikä edellytä korkea teknologian laitteita. Toimiala on maailmanlaajuisesti varsin uusi. Suomessa pellettimarkkinat ovat vielä pienet ja kehittymättömät, mutta kasvua on viime vuosina tapahtunut. Valtaosa kotimaan tuotannosta menee vientiin. Investoinnin laskentaprosessissa saadut tuotannon alkuarvot sekä kustannusrakenteen määrittelyt ovat perustana varsinaisille kannattavuuslaskelmille. Laskelmista on selvitetty investointeihin liittyvät yleisimmät taloudelliset tunnusluvut ja herkimpiä muuttujia on tutkittu ja pohdittu herkkyysanalyysiä apuna käyttäen.

Area-delay Trade-offs of Texture Decompressors for a Graphics Processing Unit

Graphics Processing Units have become a booster for the microelectronics industry. However, due to intellectual property issues, there is a serious lack of information on implementation details of the hardware architecture that is behind GPUs. For instance, the way texture is handled and decompressed in a GPU to reduce bandwidth usage has never been dealt with in depth from a hardware point of view. This work addresses a comparative study on the hardware implementation of different texture decompression algorithms for both conventional (PCs and video game consoles) and mobile platforms. Circuit synthesis is performed targeting both a reconfigurable hardware platform and a 90nm standard cell library. Area-delay trade-offs have been extensively analyzed, which allows us to compare the complexity of decompressors and thus determine suitability of algorithms for systems with limited hardware resources.

Scalable software architecture for on-line multi-camera video processing

In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhead

Aproximación a la arquitectura popular en la Mancha Baja. El caso de Manzanares

La tesis se compone de una primera parte introductoria, en la que se recogen las distintas opiniones y definiciones de la arquitectura “popular”, el estado de la cuestión, comentando los artículos y publicaciones realizados sobre la Mancha. La segunda parte profundiza en aspectos generales previos al análisis edificatorio central de la tesis, con los siguientes capítulos: -Estudio de los condicionantes físicos, históricos, socio-económicos y culturales de la comarca de la Mancha Baja. Acotando el territorio. -Una visión general sobre la arquitectura tradicional de la provincia de Ciudad Real, por comarcas. -Un estudio de las distintas tipologías edificatorias tradicionales, con ejemplos en la comarca manchega. -El análisis de materiales constructivos, elementos y sistemas utilizados en las construcciones tradicionales en la Mancha Baja. La tercera parte, desde la premisa de la representación gráfica, apoyado en un anexo con dibujos de ciento treinta y siete edificios populares de Manzanares y comarca, estudia: El trazado urbano y las casas de Manzanares; desde los levantamientos de plantas, alzados y secciones, emplazamiento en la manzana y fotografías, se realiza una descripción completa, con noventa y seis ejemplos. Además de llegar a las conclusiones derivadas del análisis de estas edificaciones, los objetivos pretendidos con este estudio serían también: Realizar un primer trabajo aproximativo, desde la visión arquitectónica, de la arquitectura tradicional manchega. Recopilar toda la información existente que pueda relacionarse con la arquitectura popular en la comarca, y citar los escritos y publicaciones de referencia para posteriores estudios. Se estudia la geomorfología, el clima, el territorio, la economía, la sociología, etc…, para obtener una información clave, además de los materiales, técnicas constructivas y morfología de las edificaciones. Se destaca el apartado de los edificios preindustriales tradicionales, como molinos de viento, de agua, palomares, pósitos y bodegas con el análisis de varios ejemplos, por su importante presencia en las poblaciones. Por último se desarrolla un amplio bloque sobre bibliografía de arquitectura popular, la consultada y la general. La arquitectura popular de la mancha baja es tapial cubierto de teja árabe, cerrada al exterior, pero abierta a grandes patios, de planta baja y cámaras altas, con elementos auxiliares de protección y acceso, que revisten la aparente simplicidad volumétrica de estos complejos, viviendas-almacén. Con un complejo programa tanto agrícola como doméstico. De gran protección frente al clima, con escasa decoración, esquemas espaciales primitivos y con mayor envergadura estructural en las dependencias agropecuarias. Una arquitectura que mezcla el uso doméstico y el productivo, pero que al evolucionar aumenta su diferenciación. Edificios que mantienen las mismas cualidades estéticas, repitiendo formas y volúmenes, pero de peculiares configuraciones espaciales, se repiten los materiales y técnicas constructivas, así como elementos arquitectónicos con pocas variaciones, pero no existen dos conjuntos similares. No podemos utilizar un ejemplo como modelo de casa manchega. Evoluciona de la casa bloque, básica y primitiva, con ejemplos escasos en las poblaciones más deprimidas, a la casa compleja, donde se separan con claridad las dependencias agropecuarias de las vivideras. Evoluciona de una casa rural, con los mismos esquemas, ya se ubique en el campo o en núcleos de población, a la casa urbana, entre medianerías, en la que se puede encontrar una transformación paralela, desarrollándose programas domésticos, más especializados, mezclados con arquitecturas cultas, con programas que reflejan las nuevas necesidades de la sociedad urbana del siglo XX. ABSTRACT The thesis is composed of a first part that is collected as introducing different views and definitions of popular architecture, the state of affairs, commenting on articles and publications carried out at the Mancha. The second part explores general issues before the main urban analysis of the thesis, with the following chapters: -A study of the geographic, historical, socio-economic and cultural conditions of the region of the Mancha Baja. Delimiting the territory -A tour with an overview of the province of Ciudad Real by regions. -A study of the different traditional building types, with examples in the region from the Mancha. -The Analysis of building materials, components and systems used in traditional buildings in the Mancha Lower The third part studies from the premise of the drawing: The urban planning of the towns to study and houses of Manzanares, from the execution of plans, elevations and sections, sites in the blocks, old photographs, a full description is made, covering a wide range of examples, highlighting the “evolution during the twentieth century, in its last quarter, buildings of popular character “, which is the ultimate aim of the thesis. In addition to reaching the conclusions drawn from the analysis cards of these buildings, the objectives pursued with this study would be also: This paper is the realization of a first rough work from the architectural vision of traditional architecture from the Mancha. To Search a work method for approaching the popular architecture, other than those made so far by other studies of historians, engineers and sociologists, with the graphical representation and the buildings would be studied like living organisms that evolve over time. To collect all the current information that It can be able to connect itself with the popular architecture in the region, and cite the writings and publications of reference for future studies. Geomorphology, climate, topography of the place is studied to obtain a key information about materials, construction techniques and morphology of the buildings. A section is opened to study the case of traditional industrial buildings like windmills, flour mill, pigeon lofts, public granary, threshing floor and cellars with the analysis of several examples; its importance is highlighted in the urban plan of the town. Finally a large block of popular literature on architecture is developed, consulted for work is distinct from the general existing on the subject. The popular architecture from the Mancha is built of rammed earth and roofs inclined of Arabic tiles, the buildings are closed to the outside, but they are open around large courtyards, and ground floor and camera high, with additional elements of protection, they are opened to patios. The manor has a complex program on agricultural and domestic activity. Large climate protection, poor decoration, quite primitive in shaping living spaces, and more structural scale in storage and processing units of agriculture-related products, mainly wine, cereal and to a lesser extent oil. These architecture combines the domestic and productive use, but which will evolve and they are distinguishing, both enclosed spaces such as courtyards. The buildings keep the same aesthetic qualities because they repeat shapes and volumes, but they maintain their spatial configuration individually; the materials, building techniques and architectural elements are repeated with slight variations, but there aren´t two identical houses. This architecture evolved from the block, basic and primitive house, with few examples in the most deprived towns, to the complex house, where agricultural units are clearly separated of domestic rooms. It developed from a country house (with the same patterns) whether it is located in the countryside or in the towns, to an urban house, in which we can find a parallel transformation, developing domestic programs, more specialized, mixed with cultivated architectures, with programs that reflect the changing needs of urban society of the twentieth century.

The Latest Prague Contributions to Written Cultural Heritage Processing

* The following text has been originally published in the Proceedings of the Language Recourses and Evaluation Conference held in Lisbon, Portugal, 2004, under the title of "Towards Intelligent Written Cultural Heritage Processing - Lexical processing". I present here a revised contribution of the aforementioned paper and I add here the latest efforts done in the Center for Computational Linguistic in Prague in the field under discussion.

Swarm intelligence for scheduling: a review

Swarm Intelligence generally refers to a problem-solving ability that emerges from the interaction of simple information-processing units. The concept of Swarm suggests multiplicity, distribution, stochasticity, randomness, and messiness. The concept of Intelligence suggests that problem-solving approach is successful considering learning, creativity, cognition capabilities. This paper introduces some of the theoretical foundations, the biological motivation and fundamental aspects of swarm intelligence based optimization techniques such Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Artificial Bees Colony (ABC) algorithms for scheduling optimization.

Embedded platform for ECG biometric recognition

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Parallel hyperspectral unmixing on GPUs

This letter presents a new parallel method for hyperspectral unmixing composed by the efficient combination of two popular methods: vertex component analysis (VCA) and sparse unmixing by variable splitting and augmented Lagrangian (SUNSAL). First, VCA extracts the endmember signatures, and then, SUNSAL is used to estimate the abundance fractions. Both techniques are highly parallelizable, which significantly reduces the computing time. A design for the commodity graphics processing units of the two methods is presented and evaluated. Experimental results obtained for simulated and real hyperspectral data sets reveal speedups up to 100 times, which grants real-time response required by many remotely sensed hyperspectral applications.

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.