Multi-objective adaptive evolutionary strategy for tuning compilations

Tuning compilations is the process of adjusting the values of a compiler options to improve some features of the final application. In this paper, a strategy based on the use of a genetic algorithm and a multi-objective scheme is proposed to deal with this task. Unlike previous works, we try to take advantage of the knowledge of this domain to provide a problem-specific genetic operation that improves both the speed of convergence and the quality of the results. The evaluation of the strategy is carried out by means of a case of study aimed to improve the performance of the well-known web server Apache. Experimental results show that a 7.5% of overall improvement can be achieved. Furthermore, the adaptive approach has shown an ability to markedly speed-up the convergence of the original strategy.

Parallel relaxed and extrapolated algorithms for computing PageRank

In this paper, parallel Relaxed and Extrapolated algorithms based on the Power method for accelerating the PageRank computation are presented. Different parallel implementations of the Power method and the proposed variants are analyzed using different data distribution strategies. The reported experiments show the behavior and effectiveness of the designed algorithms for realistic test data using either OpenMP, MPI or an hybrid OpenMP/MPI approach to exploit the benefits of shared memory inside the nodes of current SMP supercomputers.

Panorámica: serious games, gamification y mucho más

La relación entre los videojuegos y el mundo de la educación es y ha sido tormentosa, con amores y odios, con sus altibajos. Pero lo que es indudable es que los videojuegos son una realidad en el mundo actual y una potente industria. Y además, los juegos siempre han jugado un papel fundamental en la educación. Aunque su incorporación a la actividad académica no ha sido todo lo ágil que hubiera sido conveniente, los videojuegos ya forman parte de la universidad. En este artículo vamos a presentar algunas de las iniciativas que hemos llevado a cabo desde que en el año 2002 incorporamos los videojuegos en nuestras actividades académicas, tanto docentes como investigadoras. MadUniversity es un videojuego que dio lugar a varios proyectos final de carrera de la Ingeniería en Informática. Screaming Racers es un videojuego diseñado y desarrollado para ser utilizado como plataforma de experimentación de técnicas en inteligencia artificial basadas en la neuroevolución. The Conference Interpreter (CoIn) es un videojuego para la práctica del inglés desarrollado para apoyar una tesis doctoral. GameLearning es una colección de minijuegos conceptuales para la adquisición de habilidades directivas. ABPgame es la aplicación de la metodología basada en proyectos a varias asignaturas de las titulaciones de Ingeniería en Informática y del Grado en Ingeniería Multimedia que realizan un proyecto común: un videojuego. PLMan es un sistema gamificado que ayuda a desarrollar habilidades de pensamiento lógico, a través del lenguaje Prolog. Nuestro objetivo es mostrar la utilidad de los videojuegos y sus múltiples aplicaciones en el entorno universitario: como objetos de aprendizaje por medio de videojuegos educativos (serious games); como proyectos informáticos complejos para ser desarrollados por nuestros estudiantes; como entorno de experimentación para comprobar la validez de las investigaciones en inteligencia artificial; y finalmente como filosofía a aplicar al campo de la educación, lo que se ha etiquetado como gamificación.

A Model to Visualize Information in a Complex Streets’ Network

his paper discusses a process to graphically view and analyze information obtained from a network of urban streets, using an algorithm that establishes a ranking of importance of the nodes of the network itself. The basis of this process is to quantify the network information obtained by assigning numerical values to each node, representing numerically the information. These values are used to construct a data matrix that allows us to apply a classification algorithm of nodes in a network in order of importance. From this numerical ranking of the nodes, the process finish with the graphical visualization of the network. An example is shown to illustrate the whole process.

Geometric 3D point cloud compression

The use of 3D data in mobile robotics applications provides valuable information about the robot’s environment but usually the huge amount of 3D information is unmanageable by the robot storage and computing capabilities. A data compression is necessary to store and manage this information but preserving as much information as possible. In this paper, we propose a 3D lossy compression system based on plane extraction which represent the points of each scene plane as a Delaunay triangulation and a set of points/area information. The compression system can be customized to achieve different data compression or accuracy ratios. It also supports a color segmentation stage to preserve original scene color information and provides a realistic scene reconstruction. The design of the method provides a fast scene reconstruction useful for further visualization or processing tasks.

Image Noise Removal on Heterogeneous CPU-GPU Configurations

A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.

The Conference Interpreter

The Conference Interpreter es un videojuego de simulación de la labor del intérprete de conferencias, en el que se reproduce un audio en lengua inglesa y en el que, con un lapso de un segundo y medio, aparece la transcripción del audio con determinados huecos para los que el jugador ha de seleccionar entre las distintas unidades semánticas propuestas en la parte inferior de la pantalla.

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.

3D Hand Pose Estimation with Neural Networks

We propose the design of a real-time system to recognize and interprethand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of hand pose models combined with motion information provide with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirrorwriting system and to a system to estimate hand pose will be designed to demonstrate the validity of the system.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

Aplicación de Ordenadores (curso 2001-2002)

Material docente de la asignatura Aplicación de Ordenadores, de 3º curso de Ingeniería Técnica de Obras Públicas.

¿Puede un videojuego ayudarnos a predecir los resultados de aprendizaje?

Comunicación presentada en CoSECiVi 2014, I Congreso de la Sociedad Española para las Ciencias del Videojuego, Barcelona, 24 de junio de 2014.

Construction of Intelligent Virtual Worlds Using a Grammatical Framework

The potential of integrating multiagent systems and virtual environments has not been exploited to its whole extent. This paper proposes a model based on grammars, called Minerva, to construct complex virtual environments that integrate the features of agents. A virtual world is described as a set of dynamic and static elements. The static part is represented by a sequence of primitives and transformations and the dynamic elements by a series of agents. Agent activation and communication is achieved using events, created by the so-called event generators. The grammar defines a descriptive language with a simple syntax and a semantics, defined by functions. The semantics functions allow the scene to be displayed in a graphics device, and the description of the activities of the agents, including artificial intelligence algorithms and reactions to physical phenomena. To illustrate the use of Minerva, a practical example is presented: a simple robot simulator that considers the basic features of a typical robot. The result is a functional simple simulator. Minerva is a reusable, integral, and generic system, which can be easily scaled, adapted, and improved. The description of the virtual scene is independent from its representation and the elements that it interacts with.

An approach to the application of shift-and-add algorithms on engineering and industrial processes

Different kinds of algorithms can be chosen so as to compute elementary functions. Among all of them, it is worthwhile mentioning the shift-and-add algorithms due to the fact that they have been specifically designed to be very simple and to save computer resources. In fact, almost the only operations usually involved with these methods are additions and shifts, which can be easily and efficiently performed by a digital processor. Shift-and-add algorithms allow fairly good precision with low cost iterations. The most famous algorithm belonging to this type is CORDIC. CORDIC has the capability of approximating a wide variety of functions with only the help of a slight change in their iterations. In this paper, we will analyze the requirements of some engineering and industrial problems in terms of type of operands and functions to approximate. Then, we will propose the application of shift-and-add algorithms based on CORDIC to these problems. We will make a comparison between the different methods applied in terms of the precision of the results and the number of iterations required.

Crypto at the Time of Surveillance: Sharing with the Cloud

These days as we are facing extremely powerful attacks on servers over the Internet (say, by the Advanced Persistent Threat attackers or by Surveillance by powerful adversary), Shamir has claimed that “Cryptography is Ineffective”and some understood it as “Cryptography is Dead!” In this talk I will discuss the implications on cryptographic systems design while facing such strong adversaries. Is crypto dead or we need to design it better, taking into account, mathematical constraints, but also systems vulnerability constraints. Can crypto be effective at all when your computer or your cloud is penetrated? What is lost and what can be saved? These are very basic issues at this point of time, when we are facing potential loss of privacy and security.