26 resultados para Execution sermons.


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This paper describes the current prototype of the distributed CIAO system. It introduces the concepts of "teams" and "active modules" (or active objects), which conveniently encapsulate different types of functionalities desirable from a distributed system, from parallelism for achieving speedup to client-server applications. The user primitives available are presented and their implementation described. This implementation uses attributed variables and, as an example of a communication abstraction, a blackboard that follows the Linda model. Finally, the CIAO WWW interface is also briefly described. The unctionalities of the system are illustrated through examples, using the implemented primitives.

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This paper describes the current prototype of the distributed CIAO system. It introduces the concepts of "teams" and "active modules" (or active objects), which conveniently encapsulate different types of functionalities desirable from a distributed system, from parallelism for achieving speedup to client-server applications. It presents the user primitives available and describes their implementation. This implementation uses attributed variables and, as an example of a communication abstraction, a blackboard that follows the Linda model. The functionalities of the system are illustrated through examples, using the implemented primitives. The implementation of most of the primitives is also described in detail.

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This article presents in an informal way some early results on the design of a series of paradigms for visualization of the parallel execution of logic programs. The results presented here refer to the visualization of or-parallelism, as in MUSE and Aurora, deterministic dependent and-parallelism, as in Andorra-I, and independent and-parallelism as in &-Prolog. A tool has been implemented for this purpose and has been interfaced with these systems. Results are presented showing the visualization of executions from these systems and the usefulness of the resulting tool is briefly discussed.

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Effective static analyses have been proposed which allow inferring functions which bound the number of resolutions or reductions. These have the advantage of being independent from the platform on which the programs are executed and such bounds have been shown useful in a number of applications, such as granularity control in parallel execution. On the other hand, in certain distributed computation scenarios where different platforms come into play, with each platform having different capabilities, it is more interesting to express costs in metrics that include the characteristics of the platform. In particular, it is specially interesting to be able to infer upper and lower bounds on actual execution time. With this objective in mind, we propose a method which allows inferring upper and lower bounds on the execution times of procedures of a program in a given execution platform. The approach combines compile-time cost bounds analysis with a one-time profiling of the platform in order to determine the values of certain constants for that platform. These constants calibrate a cost model which from then on is able to compute statically time bound functions for procedures and to predict with a significant degree of accuracy the execution times of such procedures in the given platform. The approach has been implemented and integrated in the CiaoPP system.

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The advantages of tabled evaluation regarding program termination and reduction of complexity are well known —as are the significant implementation, portability, and maintenance efforts that some proposals (especially those based on suspension) require. This implementation effort is reduced by program transformation-based continuation call techniques, at some efficiency cost. However, the traditional formulation of this proposal by Ramesh and Cheng limits the interleaving of tabled and non-tabled predicates and thus cannot be used as-is for arbitrary programs. In this paper we present a complete translation for the continuation call technique which, using the runtime support needed for the traditional proposal, solves these problems and makes it possible to execute arbitrary tabled programs. We present performance results which show that CCall offers a useful tradeoff that can be competitive with state-of-the-art implementations.

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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.

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Provenance plays a major role when understanding and reusing the methods applied in a scientic experiment, as it provides a record of inputs, the processes carried out and the use and generation of intermediate and nal results. In the specic case of in-silico scientic experiments, a large variety of scientic workflow systems (e.g., Wings, Taverna, Galaxy, Vistrails) have been created to support scientists. All of these systems produce some sort of provenance about the executions of the workflows that encode scientic experiments. However, provenance is normally recorded at a very low level of detail, which complicates the understanding of what happened during execution. In this paper we propose an approach to automatically obtain abstractions from low-level provenance data by finding common workflow fragments on workflow execution provenance and relating them to templates. We have tested our approach with a dataset of workflows published by the Wings workflow system. Our results show that by using these kinds of abstractions we can highlight the most common abstract methods used in the executions of a repository, relating different runs and workflow templates with each other.

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This article presents in an informal way some early results on the design of a series of paradigms for visualization of the parallel execution of logic programs. The results presented here refer to the visualization of or-parallelism, as in MUSE and Aurora, deterministic dependent and-parallelism, as in Andorra-I, and independent and-parallelism as in &-Prolog. A tool has been implemented for this purpose and has been interfaced with these systems. Results are presented showing the visualization of executions from these systems and the usefulness of the resulting tool is briefly discussed.

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In this paper, we examine the issue of memory management in the parallel execution of logic programs. We concentrate on non-deterministic and-parallel schemes which we believe present a relatively general set of problems to be solved, including most of those encountered in the memory management of or-parallel systems. We present a distributed stack memory management model which allows flexible scheduling of goals. Previously proposed models (based on the "Marker model") are lacking in that they impose restrictions on the selection of goals to be executed or they may require consume a large amount of virtual memory. This paper first presents results which imply that the above mentioned shortcomings can have significant performance impacts. An extension of the Marker Model is then proposed which allows flexible scheduling of goals while keeping (virtual) memory consumption down. Measurements are presented which show the advantage of this solution. Methods for handling forward and backward execution, cut and roll back are discussed in the context of the proposed scheme. In addition, the paper shows how the same mechanism for flexible scheduling can be applied to allow the efficient handling of the very general form of suspension that can occur in systems which combine several types of and-parallelism and more sophisticated methods of executing logic programs. We believe that the results are applicable to many and- and or-parallel systems.

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Logic programming (LP) is a family of high-level programming languages which provides high expressive power. With LP, the programmer writes the properties of the result and / or executable specifications instead of detailed computation steps. Logic programming systems which feature tabled execution and constraint logic programming have been shown to increase the declarativeness and efficiency of Prolog, while at the same time making it possible to write very expressive programs. Tabled execution avoids infinite failure in some cases, while improving efficiency in programs which repeat computations. CLP reduces the search tree and brings the power of solving (in)equations over arbitrary domains. Similarly to the LP case, CLP systems can also benefit from the power of tabling. Previous implementations which take ful advantage of the ideas behind tabling (e.g., forcing suspension, answer subsumption, etc. wherever it is necessary to avoid recomputation and terminate whenever possible) did not offer a simple, well-documented, easy-to-understand interface. This would be necessary to make the integratation of arbitrary CLP solvers into existing tabling systems possible. This clearly hinders a more widespread usage of the combination of both facilities. In this thesis we examine the requirements that a constraint solver must fulfill in order to be interfaced with a tabling system. We propose and implement a framework, which we have called Mod TCLP, with a minimal set of operations (e.g., entailment checking and projection) which the constraint solver has to provide to the tabling engine. We validate the design of Mod TCLP by a series of use cases: we re-engineer a previously existing tabled constrain domain (difference constraints) which was connected in an ad-hoc manner with the tabling engine in Ciao Prolog; we integrateHolzbauer’s CLP(Q) implementationwith Ciao Prolog’s tabling engine; and we implement a constraint solver over (finite) lattices. We evaluate its performance with several benchmarks that implement a simple abstract interpreter whose fixpoint is reached by means of tabled execution, and whose domain operations are handled by the constraint over (finite) lattices, where TCLP avoids recomputing subsumed abstractions.---ABSTRACT---La programación lógica con restricciones (CLP) y la tabulación son extensiones de la programación lógica que incrementan la declaratividad y eficiencia de Prolog, al mismo tiempo que hacen posible escribir programasmás expresivos. Las implementaciones anteriores que integran completamente ambas extensiones, incluyendo la suspensión de la ejecución de objetivos siempre que sea necesario, la implementación de inclusión (subsumption) de respuestas, etc., en todos los puntos en los que sea necesario para evitar recomputaciones y garantizar la terminación cuando sea posible, no han proporcionan una interfaz simple, bien documentada y fácil de entender. Esta interfaz es necesaria para permitir integrar resolutores de CLP arbitrarios en el sistema de tabulación. Esto claramente dificulta un uso más generalizado de la integración de ambas extensiones. En esta tesis examinamos los requisitos que un resolutor de restricciones debe cumplir para ser integrado con un sistema de tabulación. Proponemos un esquema (y su implementación), que hemos llamadoMod TCLP, que requiere un reducido conjunto de operaciones (en particular, y entre otras, entailment y proyección de almacenes de restricciones) que el resolutor de restricciones debe ofrecer al sistema de tabulación. Hemos validado el diseño de Mod TCLP con una serie de casos de uso: la refactorización de un sistema de restricciones (difference constraints) previamente conectado de un modo ad-hoc con la tabulación de Ciao Prolog; la integración del sistema de restricciones CLP(Q) de Holzbauer; y la implementación de un resolutor de restricciones sobre retículos finitos. Hemos evaluado su rendimiento con varios programas de prueba, incluyendo la implementación de un intérprete abstracto que alcanza su punto fijo mediante el sistema de tabulación y en el que las operaciones en el dominio son realizadas por el resolutor de restricciones sobre retículos (finitos) donde TCLP evita la recomputación de valores abstractos de las variables ya contenidos en llamadas anteriores.

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La reproducibilidad de estudios y resultados científicos es una meta a tener en cuenta por cualquier científico a la hora de publicar el producto de una investigación. El auge de la ciencia computacional, como una forma de llevar a cabo estudios empíricos haciendo uso de modelos matemáticos y simulaciones, ha derivado en una serie de nuevos retos con respecto a la reproducibilidad de dichos experimentos. La adopción de los flujos de trabajo como método para especificar el procedimiento científico de estos experimentos, así como las iniciativas orientadas a la conservación de los datos experimentales desarrolladas en las últimas décadas, han solucionado parcialmente este problema. Sin embargo, para afrontarlo de forma completa, la conservación y reproducibilidad del equipamiento computacional asociado a los flujos de trabajo científicos deben ser tenidas en cuenta. La amplia gama de recursos hardware y software necesarios para ejecutar un flujo de trabajo científico hace que sea necesario aportar una descripción completa detallando que recursos son necesarios y como estos deben de ser configurados. En esta tesis abordamos la reproducibilidad de los entornos de ejecución para flujos de trabajo científicos, mediante su documentación usando un modelo formal que puede ser usado para obtener un entorno equivalente. Para ello, se ha propuesto un conjunto de modelos para representar y relacionar los conceptos relevantes de dichos entornos, así como un conjunto de herramientas que hacen uso de dichos módulos para generar una descripción de la infraestructura, y un algoritmo capaz de generar una nueva especificación de entorno de ejecución a partir de dicha descripción, la cual puede ser usada para recrearlo usando técnicas de virtualización. Estas contribuciones han sido aplicadas a un conjunto representativo de experimentos científicos pertenecientes a diferentes dominios de la ciencia, exponiendo cada uno de ellos diferentes requisitos hardware y software. Los resultados obtenidos muestran la viabilidad de propuesta desarrollada, reproduciendo de forma satisfactoria los experimentos estudiados en diferentes entornos de virtualización. ABSTRACT Reproducibility of scientific studies and results is a goal that every scientist must pursuit when announcing research outcomes. The rise of computational science, as a way of conducting empirical studies by using mathematical models and simulations, have opened a new range of challenges in this context. The adoption of workflows as a way of detailing the scientific procedure of these experiments, along with the experimental data conservation initiatives that have been undertaken during last decades, have partially eased this problem. However, in order to fully address it, the conservation and reproducibility of the computational equipment related to them must be also considered. The wide range of software and hardware resources required to execute a scientific workflow implies that a comprehensive description detailing what those resources are and how they are arranged is necessary. In this thesis we address the issue of reproducibility of execution environments for scientific workflows, by documenting them in a formalized way, which can be later used to obtain and equivalent one. In order to do so, we propose a set of semantic models for representing and relating the relevant information of those environments, as well as a set of tools that uses these models for generating a description of the infrastructure, and an algorithmic process that consumes these descriptions for deriving a new execution environment specification, which can be enacted into a new equivalent one using virtualization solutions. We apply these three contributions to a set of representative scientific experiments, belonging to different scientific domains, and exposing different software and hardware requirements. The obtained results prove the feasibility of the proposed approach, by successfully reproducing the target experiments under different virtualization environments.