High Performance FPGA-oriented mersenne twister uniform random number generator

Mersenne Twister (MT) uniform random number generators are key cores for hardware acceleration of Monte Carlo simulations. In this work, two different architectures are studied: besides the classical table-based architecture, a different architecture based on a circular buffer and especially targeting FPGAs is proposed. A 30% performance improvement has been obtained when compared to the fastest previous work. The applicability of the proposed MT architectures has been proven in a high performance Gaussian RNG.

Aplicación móvil para el acceso a juego de naipes sobre el desarrollo humano

Este Proyecto Fin de Carrera (PFC) tiene como objetivo el análisis, diseño e implementación de un videojuego móvil multijugador, con un enfoque educativo, para la sensibilización sobre el Índice de Desarrollo Humano (IDH). El sistema resultante se ha desarrollado para la Plataforma Android, utilizando el Framework AndEngine, que utiliza aceleración hardware de la GPU para garantizar un buen rendimiento en terminales de gama baja, de modo que pueda utilizarse en un amplio número de terminales móviles disponibles en el mercado. La aplicación se presenta como un juego de cartas con los diferentes países y sus datos humanitarios, los jugadores deben conocer el peso de los índices de desarrollo (esperanza de vida, renta, educación) de los países en comparación con los países de los otros jugadores. El sistema de juego premia a los jugadores con mayores conocimientos sobre los datos humanos de los diferentes países del mundo, de ese modo los mejores jugadores serán los que tengan más conocimientos de estos datos. El juego permite jugar partidas en solitario utilizando jugadores manejados por la CPU, o multijugador mediante WIFI o 3G. La actualización de la información y de los datos de las partidas se realiza a través de la comunicación con un servidor web ya implementado de forma complementaria a la realización de este proyecto. El sistema ha sido integrado y validado satisfactoriamente con diferentes terminales móviles y usuarios de diferente perfil de edad y uso. El videojuego se puede descargar de la página web creada en un proyecto complementario a éste (pendiente de publicación web), y ya se encuentra también disponible en Google Play. https://play.google.com/store/apps/details?id=xnetcom.pro.cartas&hl=es_419 ABSTRACT. This Project End of Career (PFC) takes as an aim the analysis, design and implementation of a multiplayer mobile videogame, with an educational approach, for the awareness on the Human Development Index (HDI). The resultant system has been developed for the Platform Android, using the AndEngine Framework, which uses hardware acceleration of the GPU to ensure a good performance on low-end terminals, so that it can be used in a wide range of mobile handsets available in the market. The application is presented as a card game with the different countries and his humanitarian information, the players must know the weight of the indexes of development (life expectancy, revenue, education) of the countries in comparison with the countries of other players. The game system rewards players with more knowledge on human information of different countries, thus the best players will be those with more knowledge of these information. The game allows to play items in solitarily using players handled by the CPU, or multiplayer by means of WIFI or 3G. The update of the information and data of the online games is done through communication with a web server implemented as a complement to the realization of this project. The system has been built and successfully validated with different mobile terminals and users of different age and usage profile. The game can be downloaded from the website created in a complementary project to this (web publication pending), and is now also available on Google Play https://play.google.com/store/apps/details?id=xnetcom.pro.cartas&hl=es_419

Explotación de servicios de la Infraestructura de Datos Espaciales de España (IDEE) en dispositivos móviles

En los últimos años el número de dispositivos móviles y smartphones ha aumentado drásticamente, así como el número de aplicaciones destinadas a estos. Los desarrolladores siempre se han visto frenados en la creación de estas aplicaciones debido a la complejidad que supone la diversidad de sistemas operativos (Android, iOS, Windows Phone, etc), que utilizan lenguajes de programación diferentes, haciendo que, para poder desarrollar una aplicación que funcione en estas plataformas, en verdad haya que implementar una aplicación independiente para cada una de las plataformas. Para solucionar este problema han surgido frameworks, como Appcelerator Titanium, que permiten escribir una sola vez la aplicación y compilarla para las diferentes plataformas móviles objetivo. Sin embargo, estos frameworks están aún en estado muy temprano de desarrollo, por lo que no resuelven toda la problemática ni dan una respuesta completa a los desarrolladores. El objetivo de este Trabajo de Fin de Grado ha sido contribuir a la evolución de estos frameworks mediante la creación de un módulo para Appcelerator Titanium que permita construir de manera ágil aplicaciones multiplataforma que hagan uso de visualizadores de información geográfica. Para ello se propone el desarrollo de un módulo de mapa con soporte para capas WMS, rutas y polígonos en WKT, KML y GeoJSON. Se facilitará además que estas aplicaciones puedan acceder a capacidades del hardware como la brújula y el GPS para realizar un seguimiento de la localización, a la vez que se hace uso de la aceleración por el hardware subyacente para mejorar la velocidad y fluidez de la información visualizada en el mapa. A partir de este módulo se ha creado una aplicación que hace uso de todas sus características y posteriormente se ha migrado a la plataforma Wirecloud4Tablet como componente nativo que puede integrarse con otros componentes web (widgets) mediante técnicas de mashup. Gracias a esto se ha podido fusionar por un lado todas las ventajas que ofrece Wirecloud para el rápido desarrollo de aplicaciones sin necesidad de tener conocimientos de programación, junto con las ventajas que ofrecen las aplicaciones nativas en cuanto a rendimiento y características extras. Usando los resultados de este proyecto, se pueden crear de manera ágil aplicaciones composicionales nativas multiplataforma que hagan uso de visualización de información geográfica; es decir, se pueden crear aplicaciones en pocos minutos y sin conocimientos de programación que pueden ejecutar diferentes componentes (como el mapa) de manera nativa en múltiples plataformas. Se facilita también la integración de componentes nativos (como es el mapa desarrollado) con otros componentes web (widgets) en un mashup que puede visualizarse en dispositivos móviles mediante la plataforma Wirecloud. ---ABSTRACT---In recent years the number of mobile devices and smartphones has increased dramatically as well as the number of applications targeted at them. Developers always have been slowed in the creation of these applications due to the complexity caused by the diversity of operating systems (Android, iOS, Windows Phone, etc), each of them using different programming languages, so that, in order to develop an application that works on these platforms, the developer really has to implement a different application for each platform. To solve this problem frameworks such as Appcelerator Titanium have emerged, allowing developers to write the application once and to compile it for different target mobile platforms. However, these frameworks are still in very early stage of development, so they do not solve all the difficulties nor give a complete solution to the developers. The objective of this final year dissertation is to contribute to the evolution of these frameworks by creating a module for Appcelerator Titanium that permits to nimbly build multi-platform applications that make use of geographical information visualization. To this end, the development of a map module with support for WMS layers, paths, and polygons in WKT, KML, and GeoJSON is proposed. This module will also facilitate these applications to access hardware capabilities such as GPS and compass to track the location, while it makes use of the underlying hardware acceleration to improve the speed and fluidity of the information displayed on the map. Based on this module, it has been created an application that makes use of all its features and subsequently it has been migrated to the platform Wirecloud4Tablet as a native component that can be integrated with other web components (widgets) using mashup techniques. As a result, it has been fused on one side all the advantages Wirecloud provides for fast application development without the need of programming skills, along with the advantages of native apps, such as performance and extra features. Using the results of this project, compositional platform native applications that make use of geographical information visualization can be created in an agile way; ie, in a few minutes and without having programming skills, a developer could create applications that can run different components (like the map) natively on multiple platforms. It also facilitates the integration of native components (like the map) with other web components (widgets) in a mashup that can be displayed on mobile devices through the Wirecloud platform.

Efficient tool path computation using multi-core GPUs

Tool path generation is one of the most complex problems in Computer Aided Manufacturing. Although some efficient strategies have been developed, most of them are only useful for standard machining. However, the algorithms used for tool path computation demand a higher computation performance, which makes the implementation on many existing systems very slow or even impractical. Hardware acceleration is an incremental solution that can be cleanly added to these systems while keeping everything else intact. It is completely transparent to the user. The cost is much lower and the development time is much shorter than replacing the computers by faster ones. This paper presents an optimisation that uses a specific graphic hardware approach using the power of multi-core Graphic Processing Units (GPUs) in order to improve the tool path computation. This improvement is applied on a highly accurate and robust tool path generation algorithm. The paper presents, as a case of study, a fully implemented algorithm used for turning lathe machining of shoe lasts. A comparative study will show the gain achieved in terms of total computing time. The execution time is almost two orders of magnitude faster than modern PCs.

Low-cost real-time gesture recognition

A major impediment to developing real-time computer vision systems has been the computational power and level of skill required to process video streams in real-time. This has meant that many researchers have either analysed video streams off-line or used expensive dedicated hardware acceleration techniques. Recent software and hardware developments have greatly eased the development burden of realtime image analysis leading to the development of portable systems using cheap PC hardware and software exploiting the Multimedia Extension (MMX) instruction set of the Intel Pentium chip. This paper describes the implementation of a computationally efficient computer vision system for recognizing hand gestures using efficient coding and MMX-acceleration to achieve real-time performance on low cost hardware.

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application

How can GPU acceleration be obtained as a service in a cluster? This question has become increasingly significant due to the inefficiency of installing GPUs on all nodes of a cluster. The research reported in this paper is motivated to address the above question by employing rCUDA (remote CUDA), a framework that facilitates Acceleration-as-a-Service (AaaS), such that the nodes of a cluster can request the acceleration of a set of remote GPUs on demand. The rCUDA framework exploits virtualisation and ensures that multiple nodes can share the same GPU. In this paper we test the feasibility of the rCUDA framework on a real-world application employed in the financial risk industry that can benefit from AaaS in the production setting. The results confirm the feasibility of rCUDA and highlight that rCUDA achieves similar performance compared to CUDA, provides consistent results, and more importantly, allows for a single application to benefit from all the GPUs available in the cluster without loosing efficiency.

Prying into the intimate secrets of animal lives; software beyond hardware for comprehensive annotation in 'Daily Diary' tags

BACKGROUND: Smart tags attached to freely-roaming animals recording multiple parameters at infra-second rates are becoming commonplace, and are transforming our understanding of the way wild animals behave. Interpretation of such data is complex and currently limits the ability of biologists to realise the value of their recorded information.

DESCRIPTION: This work presents Framework4, an all-encompassing software suite which operates on smart sensor data to determine the 4 key elements considered pivotal for movement analysis from such tags (Endangered Species Res 4: 123-37, 2008). These are; animal trajectory, behaviour, energy expenditure and quantification of the environment in which the animal moves. The program transforms smart sensor data into dead-reckoned movements, template-matched behaviours, dynamic body acceleration-derived energetics and position-linked environmental data before outputting it all into a single file. Biologists are thus left with a single data set where animal actions and environmental conditions can be linked across time and space.

CONCLUSIONS: Framework4 is a user-friendly software that assists biologists in elucidating 4 key aspects of wild animal ecology using data derived from tags with multiple sensors recording at high rates. Its use should enhance the ability of biologists to derive meaningful data rapidly from complex data.

Effects of MRI scan acceleration on brain volume measurement consistency.

PURPOSE: To evaluate the effects of recent advances in magnetic resonance imaging (MRI) radiofrequency (RF) coil and parallel imaging technology on brain volume measurement consistency. MATERIALS AND METHODS: In all, 103 whole-brain MRI volumes were acquired at a clinical 3T MRI, equipped with a 12- and 32-channel head coil, using the T1-weighted protocol as employed in the Alzheimer's Disease Neuroimaging Initiative study with parallel imaging accelerations ranging from 1 to 5. An experienced reader performed qualitative ratings of the images. For quantitative analysis, differences in composite width (CW, a measure of image similarity) and boundary shift integral (BSI, a measure of whole-brain atrophy) were calculated. RESULTS: Intra- and intersession comparisons of CW and BSI measures from scans with equal acceleration demonstrated excellent scan-rescan accuracy, even at the highest acceleration applied. Pairs-of-scans acquired with different accelerations exhibited poor scan-rescan consistency only when differences in the acceleration factor were maximized. A change in the coil hardware between compared scans was found to bias the BSI measure. CONCLUSION: The most important findings are that the accelerated acquisitions appear to be compatible with the assessment of high-quality quantitative information and that for highest scan-rescan accuracy in serial scans the acquisition protocol should be kept as consistent as possible over time. J. Magn. Reson. Imaging 2012;36:1234-1240. ©2012 Wiley Periodicals, Inc.

LALP: a language to program custom FPGA-based acceleration engines

Field-Programmable Gate Arrays (FPGAs) are becoming increasingly important in embedded and high-performance computing systems. They allow performance levels close to the ones obtained with Application-Specific Integrated Circuits, while still keeping design and implementation flexibility. However, to efficiently program FPGAs, one needs the expertise of hardware developers in order to master hardware description languages (HDLs) such as VHDL or Verilog. Attempts to furnish a high-level compilation flow (e.g., from C programs) still have to address open issues before broader efficient results can be obtained. Bearing in mind an FPGA available resources, it has been developed LALP (Language for Aggressive Loop Pipelining), a novel language to program FPGA-based accelerators, and its compilation framework, including mapping capabilities. The main ideas behind LALP are to provide a higher abstraction level than HDLs, to exploit the intrinsic parallelism of hardware resources, and to allow the programmer to control execution stages whenever the compiler techniques are unable to generate efficient implementations. Those features are particularly useful to implement loop pipelining, a well regarded technique used to accelerate computations in several application domains. This paper describes LALP, and shows how it can be used to achieve high-performance computing solutions.

FPGA Acceleration of Monte Carlo-based Financial Simulation: Design Challenges and Lessons Learnt

The simulation of interest rate derivatives is a powerful tool to face the current market fluctuations. However, the complexity of the financial models and the way they are processed require exorbitant computation times, what is in clear conflict with the need of a processing time as short as possible to operate in the financial market. To shorten the computation time of financial derivatives the use of hardware accelerators becomes a must.