High-level characteristics of or-and independent and-parallelism in prolog

Although studies of a number of parallel implementations of logic programming languages are now available, their results are difficult to interpret due to the multiplicity of factors involved, the effect of each of which is difficult to sep��rate. In this paper we present the results of a high-level simulation study of or- and independent and-parallelism with a wide selection of Prolog programs that aims to determine the intrinsic amount of parallelism, independently of implementation factors, thus facilitating this separation. We expect this study will be instrumental in better understanding and comparing results from actual implementations, as shown by some examples provided in the paper. In addition, the paper examines some of the issues and tradeoffs associated with the combination of and- and or-parallelism and proposes reasonable solutions based on the simulation data obtained.

Dise��o e implementaci��n de funcionalidades OpenMP, basadas en modelos de concurrencia desarrollados en lenguaje Go

A ra��z de la aparici��n de los procesadores dotados de varios ���cores���, la programaci��n paralela, un concepto que, por otra parte no era nada nuevo y se conoc��a desde hace d��cadas, sufri�� un nuevo impulso, pues se cre��a que se pod��a superar el techo tecnol��gico que hab��a estado limitando el rendimiento de esta programaci��n durante a��os. Este impulso se ha ido manteniendo hasta la actualidad, movido por la necesidad de sistemas cada vez m��s potentes y gracias al abaratamiento de los costes de fabricaci��n. Esta tendencia ha motivado la aparici��n de nuevo software y lenguajes con componentes orientados precisamente al campo de la programaci��n paralela. Este es el caso del lenguaje Go, desarrollado por Google y lanzado en 2009. Este lenguaje se basa en modelos de concurrencia que lo hacen muy adecuados para abordar desarrollos de naturaleza paralela. Sin embargo, la programaci��n paralela es un campo complejo y heterog��neo, y los programadores son reticentes a utilizar herramientas nuevas, en beneficio de aquellas que ya conocen y les son familiares. Un buen ejemplo son aquellas implementaciones de lenguajes conocidos, pero orientadas a programaci��n paralela, y que siguen las directrices de un est��ndar ampliamente reconocido y aceptado. Este es el caso del est��ndar OpenMP, un Interfaz de Programaci��n de Aplicaciones (API) flexible, portable y escalable, orientado a la programaci��n paralela multiproceso en arquitecturas multi-core o multinucleo. Dicho est��ndar posee actualmente implementaciones en los lenguajes C, C++ y Fortran. Este proyecto nace como un intento de aunar ambos conceptos: un lenguaje emergente con interesantes posibilidades en el campo de la programaci��n paralela, y un est��ndar reputado y ampliamente extendido, con el que los programadores se encuentran familiarizados. El objetivo principal es el desarrollo de un conjunto de librer��as del sistema (que engloben directivas de compilaci��n o pragmas, librer��as de ejecuci��n y variables de entorno), soportadas por las caracter��sticas y los modelos de concurrencia propios de Go; y que a��adan funcionalidades propias del est��ndar OpenMP. La idea es a��adir funcionalidades que permitan programar en lenguaje Go utilizando la sintaxis que OpenMP proporciona para otros lenguajes, como Fortan y C/C++ (concretamente, similar a esta ��ltima), y, de esta forma, dotar al usuario de Go de herramientas para programar estructuras de procesamiento paralelo de forma sencilla y transparente, de la misma manera que lo har��a utilizando C/C++.---ABSTRACT---As a result of the appearance of processors equipped with multiple "cores ", parallel programming, a concept which, moreover, it was not new and it was known for decades, suffered a new impulse, because it was believed they could overcome the technological ceiling had been limiting the performance of this program for years. This impulse has been maintained until today, driven by the need for ever more powerful systems and thanks to the decrease in manufacturing costs. This trend has led to the emergence of new software and languages with components guided specifically to the field of parallel programming. This is the case of Go language, developed by Google and released in 2009. This language is based on concurrency models that make it well suited to tackle developments in parallel nature. However, parallel programming is a complex and heterogeneous field, and developers are reluctant to use new tools to benefit those who already know and are familiar. A good example are those implementations from well-known languages, but parallel programming oriented, and witch follow the guidelines of a standard widely recognized and accepted. This is the case of the OpenMP standard, an application programming interface (API), flexible, portable and scalable, parallel programming oriented, and designed for multi-core architectures. This standard currently has implementations in C, C ++ and Fortran. This project was born as an attempt to combine two concepts: an emerging language, with interesting possibilities in the field of parallel programming, and a reputed and widespread standard, with which programmers are familiar with. The main objective is to develop a set of system libraries (which includes compiler directives or pragmas, runtime libraries and environment variables), supported by the characteristics and concurrency patterns of Go; and that add custom features from the OpenMP standard. The idea is to add features that allow programming in Go language using the syntax OpenMP provides for other languages, like Fortran and C / C ++ (specifically, similar to the latter ), and, in this way, provide Go users with tools for programming parallel structures easily and, in the same way they would using C / C ++.

An experiment on CAI sequencing constructs /

Includes bibliographical references.

The University of Illinois attached machine operating system: design criteria and program logic,

"Supported in part by National Science Foundation under Grant No. NSF-GP-7634."

Burst processing /

Cover title.

Well-founded orderings for proving termination of systems of rewrite rules /

Bibliography: p. 34.

Feasibility studies of an on-line identification technique

This thesis is concerned with the study of a non-sequential identification technique, so that it may be applied to the identification of process plant mathematical models from process measurements with the greatest degree of accuracy and reliability. In order to study the accuracy of the technique under differing conditions, simple mathematical models were set up on a parallel hybrid. computer and these models identified from input/output measurements by a small on-line digital computer. Initially, the simulated models were identified on-line. However, this method of operation was found not suitable for a thorough study of the technique due to equipment limitations. Further analysis was carried out in a large off-line computer using data generated by the small on-line computer. Hence identification was not strictly on-line. Results of the work have shovm that the identification technique may be successfully applied in practice. An optimum sampling period is suggested, together with noise level limitations for maximum accuracy. A description of a double-effect evaporator is included in this thesis. It is proposed that the next stage in the work will be the identification of a mathematical model of this evaporator using the teclmique described.

Services for Satellite Data Processing

Data processing services for Meteosat geostationary satellite are presented. Implemented services correspond to the different levels of remote-sensing data processing, including noise reduction at preprocessing level, cloud mask extraction at low-level and fractal dimension estimation at high-level. Cloud mask obtained as a result of Markovian segmentation of infrared data. To overcome high computation complexity of Markovian segmentation parallel algorithm is developed. Fractal dimension of Meteosat data estimated using fractional Brownian motion models.

Scaling geospatial searches in large spatial databases

Modern geographical databases, which are at the core of geographic information systems (GIS), store a rich set of aspatial attributes in addition to geographic data. Typically, aspatial information comes in textual and numeric format. Retrieving information constrained on spatial and aspatial data from geodatabases provides GIS users the ability to perform more interesting spatial analyses, and for applications to support composite location-aware searches; for example, in a real estate database: ���Find the nearest homes for sale to my current location that have backyard and whose prices are between $50,000 and $80,000���. Efficient processing of such queries require combined indexing strategies of multiple types of data. Existing spatial query engines commonly apply a two-filter approach (spatial filter followed by nonspatial filter, or viceversa), which can incur large performance overheads. On the other hand, more recently, the amount of geolocation data has grown rapidly in databases due in part to advances in geolocation technologies (e.g., GPS-enabled smartphones) that allow users to associate location data to objects or events. The latter poses potential data ingestion challenges of large data volumes for practical GIS databases. In this dissertation, we first show how indexing spatial data with R-trees (a typical data pre-processing task) can be scaled in MapReduce���a widely-adopted parallel programming model for data intensive problems. The evaluation of our algorithms in a Hadoop cluster showed close to linear scalability in building R-tree indexes. Subsequently, we develop efficient algorithms for processing spatial queries with aspatial conditions. Novel techniques for simultaneously indexing spatial with textual and numeric data are developed to that end. Experimental evaluations with real-world, large spatial datasets measured query response times within the sub-second range for most cases, and up to a few seconds for a small number of cases, which is reasonable for interactive applications. Overall, the previous results show that the MapReduce parallel model is suitable for indexing tasks in spatial databases, and the adequate combination of spatial and aspatial attribute indexes can attain acceptable response times for interactive spatial queries with constraints on aspatial data.

ASDN : Automated Software Design Notebook tool

Software Engineering is one of the most widely researched areas of Computer Science. The ability to reuse software, much like reuse of hardware components is one of the key issues in software development. The object-oriented programming methodology is revolutionary in that it promotes software reusability. This thesis describes the development of a tool that helps programmers to design and implement software from within the Smalltalk Environment (an Object- Oriented programming environment). The ASDN tool is part of the PEREAM (Programming Environment for the Reuse and Evolution of Abstract Models) system, which advocates incremental development of software. The Asdn tool along with the PEREAM system seeks to enhance the Smalltalk programming environment by providing facilities for structured development of abstractions (concepts). It produces a document that describes the abstractions that are developed using this tool. The features of the ASDN tool are illustrated by an example.

On the Virtualization of CUDA Based GPU Remoting on ARM and X86 Machines in the GVirtuS Framework

The astonishing development of diverse and different hardware platforms is twofold: on one side, the challenge for the exascale performance for big data processing and management; on the other side, the mobile and embedded devices for data collection and human machine interaction. This drove to a highly hierarchical evolution of programming models. GVirtuS is the general virtualization system developed in 2009 and firstly introduced in 2010 enabling a completely transparent layer among GPUs and VMs. This paper shows the latest achievements and developments of GVirtuS, now supporting CUDA 6.5, memory management and scheduling. Thanks to the new and improved remoting capabilities, GVirtus now enables GPU sharing among physical and virtual machines based on x86 and ARM CPUs on local workstations,computing clusters and distributed cloud appliances.

A Scalable General Purpose System for Large-Scale Graph Processing

Graph analytics is an important and computationally demanding class of data analytics. It is essential to balance scalability, ease-of-use and high performance in large scale graph analytics. As such, it is necessary to hide the complexity of parallelism, data distribution and memory locality behind an abstract interface. The aim of this work is to build a scalable graph analytics framework that does not demand significant parallel programming experience based on NUMA-awareness.<br/>The realization of such a system faces two key problems:<br/>(i)~how to develop a scale-free parallel programming framework that scales efficiently across NUMA domains; (ii)~how to efficiently apply graph partitioning in order to create separate and largely independent work items that can be distributed among threads.<br/>

Engineering Agent-Oriented Technologies and Programming Languages for Computer Programming and Software Development

Mainstream hardware is becoming parallel, heterogeneous, and distributed on every desk, every home and in every pocket. As a consequence, in the last years software is having an epochal turn toward concurrency, distribution, interaction which is pushed by the evolution of hardware architectures and the growing of network availability. This calls for introducing further abstraction layers on top of those provided by classical mainstream programming paradigms, to tackle more effectively the new complexities that developers have to face in everyday programming. A convergence it is recognizable in the mainstream toward the adoption of the actor paradigm as a mean to unite object-oriented programming and concurrency. Nevertheless, we argue that the actor paradigm can only be considered a good starting point to provide a more comprehensive response to such a fundamental and radical change in software development. Accordingly, the main objective of this thesis is to propose Agent-Oriented Programming (AOP) as a high-level general purpose programming paradigm, natural evolution of actors and objects, introducing a further level of human-inspired concepts for programming software systems, meant to simplify the design and programming of concurrent, distributed, reactive/interactive programs. To this end, in the dissertation first we construct the required background by studying the state-of-the-art of both actor-oriented and agent-oriented programming, and then we focus on the engineering of integrated programming technologies for developing agent-based systems in their classical application domains: artificial intelligence and distributed artificial intelligence. Then, we shift the perspective moving from the development of intelligent software systems, toward general purpose software development. Using the expertise maturated during the phase of background construction, we introduce a general-purpose programming language named simpAL, which founds its roots on general principles and practices of software development, and at the same time provides an agent-oriented level of abstraction for the engineering of general purpose software systems.

Designing a high performance parallel logic programming system

Compilation techniques such as those portrayed by the Warren Abstract Machine(WAM) have greatly improved the speed of execution of logic programs. The research presented herein is geared towards providing additional performance to logic programs through the use of parallelism, while preserving the conventional semantics of logic languages. Two ��reas to which special attention is given are the preservation of sequential performance and storage efficiency, and the use of low overhead mechanisms for controlling parallel execution. Accordingly, the techniques used for supporting parallelism are efficient extensions of those which have brought high inferencing speeds to sequential implementations. At a lower level, special attention is also given to design and simulation detail and to the architectural implications of the execution model behavior. This paper offers an overview of the basic concepts and techniques used in the parallel design, simulation tools used, and some of the results obtained to date.

An abstract machine based execution model for computer architecture design and efficient implementation of logic programs in parallel.

The term "Logic Programming" refers to a variety of computer languages and execution models which are based on the traditional concept of Symbolic Logic. The expressive power of these languages offers promise to be of great assistance in facing the programming challenges of present and future symbolic processing applications in Artificial Intelligence, Knowledge-based systems, and many other areas of computing. The sequential execution speed of logic programs has been greatly improved since the advent of the first interpreters. However, higher inference speeds are still required in order to meet the demands of applications such as those contemplated for next generation computer systems. The execution of logic programs in parallel is currently considered a promising strategy for attaining such inference speeds. Logic Programming in turn appears as a suitable programming paradigm for parallel architectures because of the many opportunities for parallel execution present in the implementation of logic programs. This dissertation presents an efficient parallel execution model for logic programs. The model is described from the source language level down to an "Abstract Machine" level suitable for direct implementation on existing parallel systems or for the design of special purpose parallel architectures. Few assumptions are made at the source language level and therefore the techniques developed and the general Abstract Machine design are applicable to a variety of logic (and also functional) languages. These techniques offer efficient solutions to several areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the detection and handling of variable binding conflicts in AND-Parallelism, the specification of control and management of the execution tree, the treatment of distributed backtracking, and goal scheduling and memory management issues, etc. A parallel Abstract Machine design is offered, specifying data areas, operation, and a suitable instruction set. This design is based on extending to a parallel environment the techniques introduced by the Warren Abstract Machine, which have already made very fast and space efficient sequential systems a reality. Therefore, the model herein presented is capable of retaining sequential execution speed similar to that of high performance sequential systems, while extracting additional gains in speed by efficiently implementing parallel execution. These claims are supported by simulations of the Abstract Machine on sample programs.