Desarrollo de entorno online de programación para computación natural

Máster en Investigación e Innovación en Tecnologías de la Información y las Comunicaciones (i2- TIC).This work proposes a natural computer programming (for CA and NEPs) environment platform using Blockly. The platform is a web-based tool that provides simulators for two well-known natural computing systems: Cellular Automata (CA) and Network of Evolutionary Processors (NEPs). CA programming blocks presented in this work provide the ability to design and implement several types of CA including Elementary cellular automata, 2D cellular automata, and nD cellular automata. The tool also provides a graphical representation of CA’s grid through projection for any CA that has 3 or more dimensions. A NEPs Blockly programming environment is presented in this work. It provides the ability to design and simulate NEPs. Blocks are used as flexible user interface to enter NEPs specifications. The blocks automatically generate a standard XML configurations code which can be sent to the server side of the simulator for implementation. The tool also provides a graphical representation for the static topology of the system. Both CA and NEPs Blockly programming environments have been tested in several rather academic examples. The work presents an online simulation platform for natural computing algorithm using visual programing tool, namely Blockly. The proposed platform provides software engineering tools for setting up algorithms and also ease of use especially for teaching of these algorithm. The software engineering tools has been implemented on the NEPs as there is much more software tools already presented for cellular automata. The software designed for NEPs are a set of blocks to implement several types of connections between nodes. These blocks reduce time and complexity in setting up NEPs with fully connected nodes, for instance. In the other hand, cellular automata algorithm has been chosen to test the ease of the process of teaching and learning natural computing algorithms as they are much better-known model. The test has been conducted with students, teachers and researchers. Results of the experiment showed that the CA Blockly simulator outperforms traditional manual methods of implementing CA. It also showed that the proposed environment has desired features such as ease of use and decreases learning time. The NEPs part of the system has been tested against several applications. It showed that it provides a flexible designing tool for NEPs. It outperforms traditional XML coding methods in terms of ease of use and designing time. In addition we have designed specific high level constructs that automatize in some way the specific of complex NEPs’ topologies by hand. They could be considered as embryonic software engineering tools to program NEPs. Our tool is considered a generic platform for web-based implementation. It has desired features and wide range of properties that could attract the scientific community to adapt and develop in the future

Cooperative Game Theory within Multi-Agent Systems for Systems Scheduling

Research concerning organization and coordination within multi-agent systems continues to draw from a variety of architectures and methodologies. The work presented in this paper combines techniques from game theory and multi-agent systems to produce self-organizing, polymorphic, lightweight, embedded agents for systems scheduling within a large-scale real-time systems environment. Results show how this approach is used to experimentally produce optimum real-time scheduling through the emergent behavior of thousands of agents. These results are obtained using a SWARM simulation of systems scheduling within a High Energy Physics experiment consisting of 2500 digital signal processors.Comment: Fourth International Conference on Hybrid Intelligent Systems (HIS), Kitakyushu, Japan, December, 200

Probabilistic Graphical Models on Multi-Core CPUs using Java 8

In this paper, we discuss software design issues related to the development of parallel computational intelligence algorithms on multi-core CPUs, using the new Java 8 functional programming features. In particular, we focus on probabilistic graphical models (PGMs) and present the parallelisation of a collection of algorithms that deal with inference and learning of PGMs from data. Namely, maximum likelihood estimation, importance sampling, and greedy search for solving combinatorial optimisation problems. Through these concrete examples, we tackle the problem of defining efficient data structures for PGMs and parallel processing of same-size batches of data sets using Java 8 features. We also provide straightforward techniques to code parallel algorithms that seamlessly exploit multi-core processors. The experimental analysis, carried out using our open source AMIDST (Analysis of MassIve Data STreams) Java toolbox, shows the merits of the proposed solutions.Comment: Pre-print version of the paper presented in the special issue on Computational Intelligence Software at IEEE Computational Intelligence Magazine journa

Workshop proceedings: Information Systems for Space Astrophysics in the 21st Century, volume 1

The Astrophysical Information Systems Workshop was one of the three Integrated Technology Planning workshops. Its objectives were to develop an understanding of future mission requirements for information systems, the potential role of technology in meeting these requirements, and the areas in which NASA investment might have the greatest impact. Workshop participants were briefed on the astrophysical mission set with an emphasis on those missions that drive information systems technology, the existing NASA space-science operations infrastructure, and the ongoing and planned NASA information systems technology programs. Program plans and recommendations were prepared in five technical areas: Mission Planning and Operations; Space-Borne Data Processing; Space-to-Earth Communications; Science Data Systems; and Data Analysis, Integration, and Visualization

Programmable photonics : an opportunity for an accessible large-volume PIC ecosystem

We look at the opportunities presented by the new concepts of generic programmable photonic integrated circuits (PIC) to deploy photonics on a larger scale. Programmable PICs consist of waveguide meshes of tunable couplers and phase shifters that can be reconfigured in software to define diverse functions and arbitrary connectivity between the input and output ports. Off-the-shelf programmable PICs can dramatically shorten the development time and deployment costs of new photonic products, as they bypass the design-fabrication cycle of a custom PIC. These chips, which actually consist of an entire technology stack of photonics, electronics packaging and software, can potentially be manufactured cheaper and in larger volumes than application-specific PICs. We look into the technology requirements of these generic programmable PICs and discuss the economy of scale. Finally, we make a qualitative analysis of the possible application spaces where generic programmable PICs can play an enabling role, especially to companies who do not have an in-depth background in PIC technology