Estrategias Avanzadas de Tabulación y Paralelismo en Programas Lógicos = Advanced Evaluation Strategies for Tabling and Parallelism in Logic Programs

Dentro de los paradigmas de programación en el mundo de la informática tenemos la "Programación Lógica'', cuyo principal exponente es el lenguaje Prolog. Los programas Prolog se componen de un conjunto de predicados, cada uno de ellos definido en base a reglas que aportan un elevado nivel de abstracción y declaratividad al programador. Sin embargo, las formulación con reglas implica, frecuentemente, que un predicado se recompute varias veces para la misma consulta y además, Prolog utiliza un orden fijo para evaluar reglas y objetivos (evaluación SLD) que puede entrar en "bucles infinitos'' cuando ejecuta reglas recursivas declarativamente correctas. Estas limitaciones son atacadas de raiz por la tabulación, que se basa en "recordar'' en una tabla las llamadas realizadas y sus soluciones. Así, en caso de repetir una llamada tendríamos ya disponibles sus soluciones y evitamos la recomputación. También evita "bucles infinitos'' ya que las llamadas que los generan son suspendidas, quedando a la espera de que se computen soluciones para las mismas. La implementación de la tabulación no es sencilla. En particular, necesita de tres operaciones que no pueden ser ejecutadas en tiempo constante simultáneamente. Dichas operaciones son: suspensión de llamadas, relanzamiento de llamadas y {acceso a variables. La primera parte de la tesis compara tres implementaciones de tabulación sobre Ciao, cada una de las cuales penaliza una de estas operaciones. Por tanto, cada solución tiene sus ventajas y sus inconvenientes y se comportan mejor o peor dependiendo del programa ejecutado. La segunda parte de la tesis mejora la funcionalidad de la tabulación para combinarla con restricciones y también para evitar computaciones innecesarias. La programación con restricciones permite la resolución de ecuaciones como medio de programar, mecanismo altamente declarativo. Hemos desarrollado un framework para combinar la tabulación con las restricciones, priorizando objetivos como la flexibilidad, la eficiencia y la generalidad de nuestra solución, obteniendo una sinergia entre ambas técnicas que puede ser aplicada en numerosas aplicaciones. Por otra parte, un aspecto fundamental de la tabulación hace referencia al momento en que se retornan las soluciones de una llamada tabulada. Local evaluation devuelve soluciones cuando todas las soluciones de la llamada tabulada han sido computadas. Por contra, batched evaluation devuelve las soluciones una a una conforme van siendo computadas, por lo que se adapta mejor a problemas donde no nos interesa encontrar todas las soluciones. Sin embargo, su consumo de memoria es exponencialmente peor que el de local evaluation. La tesis presenta swapping evaluation, que devuelve soluciones tan pronto como son computadas pero con un consumo de memoria similar a la de local evaluation. Además, se implementan operadores de poda, once/1, para descartar la búsqueda de soluciones alternativas cuando encontramos la solución deseada. Por último, Prolog adopta con relativa facilidad soluciones para paralelismo gracias a su flexibilidad en el control de la ejecución y a que sus asignaciones son lógicas. La tercera parte de la tesis extiende el paralelismo conjuntivo de Ciao para trabajar con programas no deterministas, lo que presenta dos problemas principales: los objetivos atrapados y la recomputación de objetivos. Las soluciones clásicas para los objetivos atrapados rompían muchos invariantes de la ejecución Prolog, siendo soluciones difíciles de mantener y de extender, que la experiencia nos dice que han caído en desuso. Nosotros proponemos una solución modular (basada en la implementación de swapping evaluation), localizada y que no rompe los invariantes de la ejecución Prolog, pero que mantiene un alto rendimiento de la ejecución paralela. En referencia a la recomputación de objetivos paralelos en presencia de no determinismo hemos adaptado ténicas derivadas de la tabulación para memorizar computaciones de estos objetivos y evitar su recomputación.

Implementation of an event driven scheme for visualizing parallel execution of logic programs

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.

Some considerations on the compile-time analysis of constraint logic programs

This paper discusses some issues which arise in the dataflow analysis of constraint logic programming (CLP) languages. The basic technique applied is that of abstract interpretation. First, some types of optimizations possible in a number of CLP systems (including efficient parallelization) are presented and the information that has to be obtained at compile-time in order to be able to implement such optimizations is considered. Two approaches are then proposed and discussed for obtaining this information for a CLP program: one based on an analysis of a CLP metainterpreter using standard Prolog analysis tools, and a second one based on direct analysis of the CLP program. For the second approach an abstract domain which approximates groundness (also referred to as "definiteness") information (i.e. constraint to a single valué) and the related abstraction functions are presented.

Analysis of concurrent constraint logic programs with a fixed scheduling rule

The analysis of concurrent constraint programs is a challenge due to the inherently concurrent behaviour of its computational model. However, most implementations of the concurrent paradigm can be viewed as a computation with a fixed scheduling rule which suspends some goals so that their execution is postponed until some condition awakens them. For a certain kind of properties, an analysis defined in these terms is correct. Furthermore, it is much more tractable, and in addition can make use of existing analysis technology for the underlying fixed computation rule. We show how this can be done when the starting point is a framework for the analysis of sequential programs. The resulting analysis, which incorporates suspensions, is adequate for concurrent models where concurrency is localized, e.g. the Andorra model. We refine the analysis for this particular case. Another model in which concurrency is preferably encapsulated, and thus suspensions are local to parts of the computation, is that of CIAO. Nonetheless, the analysis scheme can be generalized to models with global concurrency. We also sketch how this could be done, and we show how the resulting analysis framework could be used for analyzing typical properties, such as suspensión freeness.

An approach to profiling for run-time checking of computational properties and performance debugging in logic programs.

Although several profiling techniques for identifying performance bottlenecks in logic programs have been developed, they are generally not automatic and in most cases they do not provide enough information for identifying the root causes of such bottlenecks. This complicates using their results for guiding performance improvement. We present a profiling method and tool that provides such explanations. Our profiler associates cost centers to certain program elements and can measure different types of resource-related properties that affect performance, preserving the precedence of cost centers in the call graph. It includes an automatic method for detecting procedures that are performance bottlenecks. The profiling tool has been integrated in a previously developed run-time checking framework to allow verification of certain properties when they cannot be verified statically. The approach allows checking global computational properties which require complex instrumentation tracking information about previous execution states, such as, e.g., that the execution time accumulated by a given procedure is not greater than a given bound. We have built a prototype implementation, integrated it in the Ciao/CiaoPP system and successfully applied it to performance improvement, automatic optimization (e.g., resource-aware specialization of programs), run-time checking, and debugging of global computational properties (e.g., resource usage) in Prolog programs.

Automatic unrestricted independent and-parallelism in logic programs

We present new algorithms which perform automatic parallelization via source-to-source transformations. The objective is to exploit goal-level, unrestricted independent andparallelism. The proposed algorithms use as targets new parallel execution primitives which are simpler and more flexible than the well-known &/2 parallel operator, which makes it possible to generate better parallel expressions by exposing more potential parallelism among the literals of a clause than is possible with &/2. The main differences between the algorithms stem from whether the order of the solutions obtained is preserved or not, and on the use of determinacy information. We briefly describe the environment where the algorithms have been implemented and the runtime platform in which the parallelized programs are executed. We also report on an evaluation of an implementation of our approach. We compare the performance obtained to that of previous annotation algorithms and show that relevant improvements can be obtained.

Precise set sharin analysis for java-style programs (and proofs).

Finding useful sharing information between instances in object- oriented programs has recently been the focus of much research. The applications of such static analysis are multiple: by knowing which variables definitely do not share in memory we can apply conventional compiler optimizations, find coarse-grained parallelism opportunities, or, more importantly, verify certain correctness aspects of programs even in the absence of annotations. In this paper we introduce a framework for deriving precise sharing information based on abstract interpretation for a Java-like language. Our analysis achieves precision in various ways, including supporting multivariance, which allows separating different contexts. We propose a combined Set Sharing + Nullity + Classes domain which captures which instances do not share and which ones are definitively null, and which uses the classes to refine the static information when inheritance is present. The use of a set sharing abstraction allows a more precise representation of the existing sharings and is crucial in achieving precision during interprocedural analysis. Carrying the domains in a combined way facilitates the interaction among them in the presence of multivariance in the analysis. We show through examples and experimentally that both the set sharing part of the domain as well as the combined domain provide more accurate information than previous work based on pair sharing domains, at reasonable cost.

Combining static analysis and profiling for estimating execution times in logic programs

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.

A generic, context sensitive analysis framework for object oriented programs

Abstract interpreters rely on the existence of a nxpoint algorithm that calculates a least upper bound approximation of the semantics of the program. Usually, that algorithm is described in terms of the particular language in study and therefore it is not directly applicable to programs written in a different source language. In this paper we introduce a generic, block-based, and uniform representation of the program control flow graph and a language-independent nxpoint algorithm that can be applied to a variety of languages and, in particular, Java. Two major characteristics of our approach are accuracy (obtained through a topdown, context sensitive approach) and reasonable efficiency (achieved by means of memoization and dependency tracking techniques). We have also implemented the proposed framework and show some initial experimental results for standard benchmarks, which further support the feasibility of the solution adopted.

Optimization of logic programs with dynamic scheduling

Dynamic scheduling increases the expressive power of logic programming languages, but also introduces some overhead. In this paper we present two classes of program transformations designed to reduce this additional overhead, while preserving the operational semantics of the original programs, modulo ordering of literals woken at the same time. The first class of transformations simplifies the delay conditions while the second class moves delayed literals later in the rule body. Application of the program transformations can be automated using information provided by compile-time analysis. We provide experimental results obtained from an implementation of the proposed techniques using the CIAO prototype compiler. Our results show that the techniques can lead to substantial performance improvement.

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.

Inferring determinacy and mutual exclusion in logic programs using mode and type analysis.

We propose an analysis for detecting procedures and goals that are deterministic (i.e., that produce at most one solution at most once), or predicates whose clause tests are mutually exclusive (which implies that at most one of their clauses will succeed) even if they are not deterministic. The analysis takes advantage of the pruning operator in order to improve the detection of mutual exclusion and determinacy. It also supports arithmetic equations and disequations, as well as equations and disequations on terms, for which we give a complete satisfiability testing algorithm, w.r.t. available type information. We have implemented the analysis and integrated it in the CiaoPP system, which also infers automatically the mode and type information that our analysis takes as input. Experiments performed on this implementation show that the analysis is fairly accurate and efficient.

Specialization and optimization of constraint programs with dynamic scheduling

In this report we discuss some of the issues involved in the specialization and optimization of constraint logic programs with dynamic scheduling. Dynamic scheduling, as any other form of concurrency, increases the expressive power of constraint logic programs, but also introduces run-time overhead. The objective of the specialization and optimization is to reduce as much as possible such overhead automatically, while preserving the semantics of the original programs. This is done by program transformation based on global analysis. We present implementation techniques for this purpose and report on experimental results obtained from an implementation of the techniques in the context of the CIAO compiler.

Implementation of an event driven scheme for visualizing parallel execution of logic programs.

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.

Automatic compile-time parallelization of CLP programs by analysis and transformation to a concurrent constraint language.

The concept of independence has been recently generalized to the constraint logic programming (CLP) paradigm. Also, several abstract domains specifically designed for CLP languages, and whose information can be used to detect the generalized independence conditions, have been recently defined. As a result we are now in a position where automatic parallelization of CLP programs is feasible. In this paper we study the task of automatically parallelizing CLP programs based on such analyses, by transforming them to explicitly concurrent programs in our parallel CC platform (CIAO) as well as to AKL. We describe the analysis and transformation process, and study its efficiency, accuracy, and effectiveness in program parallelization. The information gathered by the analyzers is evaluated not only in terms of its accuracy, i.e. its ability to determine the actual dependencies among the program variables, but also of its effectiveness, measured in terms of code reduction in the resulting parallelized programs. Given that only a few abstract domains have been already defined for CLP, and that none of them were specifically designed for dependency detection, the aim of the evaluation is not only to asses the effectiveness of the available domains, but also to study what additional information it would be desirable to infer, and what domains would be appropriate for further improving the parallelization process.