A generic framework for the analysis and specialization of logic programs

The relationship between abstract interpretation and partial deduction has received considerable attention and (partial) integrations have been proposed starting from both the partial deduction and abstract interpretation perspectives. In this work we present what we argüe is the first fully described generic algorithm for efñcient and precise integration of abstract interpretation and partial deduction. Taking as starting point state-of-the-art algorithms for context-sensitive, polyvariant abstract interpretation and (abstract) partial deduction, we present an algorithm which combines the best of both worlds. Key ingredients include the accurate success propagation inherent to abstract interpretation and the powerful program transformations achievable by partial deduction. In our algorithm, the calis which appear in the analysis graph are not analyzed w.r.t. the original definition of the procedure but w.r.t. specialized definitions of these procedures. Such specialized definitions are obtained by applying both unfolding and abstract executability. Our framework is parametric w.r.t. different control strategies and abstract domains. Different combinations of such parameters correspond to existing algorithms for program analysis and specialization. Simultaneously, our approach opens the door to the efñcient computation of strictly more precise results than those achievable by each of the individual techniques. The algorithm is now one of the key components of the CiaoPP analysis and specialization system.

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.

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.

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.

Incremental analysis of logic programs

Global analyzers traditionally read and analyze the entire program at once, in a non-incremental way. However, there are many situations which are not well suited to this simple model and which instead require reanalysis of certain parts of a program which has already been analyzed. In these cases, it appears inefficient to perform the analysis of the program again from scratch, as needs to be done with current systems. We describe how the fixpoint algorithms in current generic analysis engines can be extended to support incremental analysis. The possible changes to a program are classified into three types: addition, deletion, and arbitrary change. For each one of these, we provide one or more algorithms for identifying the parts of the analysis that must be recomputed and for performing the actual recomputation. The potential benefits and drawbacks of these algorithms are discussed. Finally, we present some experimental results obtained with an implementation of the algorithms in the PLAI generic abstract interpretation framework. The results show significant benefits when using the proposed incremental analysis algorithms.

A proposal for a flexible scheduling and memory management scheme for non-deterministic, andparallel execution of logic programs

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.

Deriving a fixpoint computation algorithm for top-down abstract interpretation of logic programs

Bruynooghe described a framework for the top-down abstract interpretation of logic programs. In this framework, abstract interpretation is carried out by constructing an abstract and-or tree in a top-down fashion for a given query and program. Such an abstract interpreter requires fixpoint computation for programs which contain recursive predicates. This paper presents in detail a fixpoint algorithm that has been developed for this purpose and the motivation behind it. We start off by describing a simple-minded algorithm. After pointing out its shortcomings, we present a series of refinements to this algorithm, until we reach the final version. The aim is to give an intuitive grasp and provide justification for the relative complexity of the final algorithm. We also present an informal proof of correctness of the algorithm and some results obtained from an implementation.

Towards an abstract domain for resource analysis of logic programs using sized types

We present a novel general resource analysis for logic programs based on sized types.Sized types are representations that incorporate structural (shape) information and allow expressing both lower and upper bounds on the size of a set of terms and their subterms at any position and depth. They also allow relating the sizes of terms and subterms occurring at different argument positions in logic predicates. Using these sized types, the resource analysis can infer both lower and upper bounds on the resources used by all the procedures in a program as functions on input term (and subterm) sizes, overcoming limitations of existing analyses and enhancing their precision. Our new resource analysis has been developed within the abstract interpretation framework, as an extension of the sized types abstract domain, and has been integrated into the Ciao preprocessor, CiaoPP. The abstract domain operations are integrated with the setting up and solving of recurrence equations for both, inferring size and resource usage functions. We show that the analysis is an improvement over the previous resource analysis present in CiaoPP and compares well in power to state of the art systems.

Resource usage analysis of logic programs via abstract interpretation using sized types

We present a novel general resource analysis for logic programs based on sized types. Sized types are representations that incorporate structural (shape) information and allow expressing both lower and upper bounds on the size of a set of terms and their subterms at any position and depth. They also allow relating the sizes of terms and subterms occurring at different argument positions in logic predicates. Using these sized types, the resource analysis can infer both lower and upper bounds on the resources used by all the procedures in a program as functions on input term (and subterm) sizes, overcoming limitations of existing resource analyses and enhancing their precision. Our new resource analysis has been developed within the abstract interpretation framework, as an extension of the sized types abstract domain, and has been integrated into the Ciao preprocessor, CiaoPP. The abstract domain operations are integrated with the setting up and solving of recurrence equations for inferring both size and resource usage functions. We show that the analysis is an improvement over the previous resource analysis present in CiaoPP and compares well in power to state of the art systems.

Implementation of multiple specialization in logic programs

We study the múltiple specialization of logic programs based on abstract interpretation. This involves in general generating several versions of a program predícate for different uses of such predícate, making use of information obtained from global analysis performed by an abstract interpreter, and finally producing a new, "multiply specialized" program. While the topic of múltiple specialization of logic programs has received considerable theoretical attention, it has never been actually incorporated in a compiler and its effects quantified. We perform such a study in the context of a parallelizing compiler and show that it is indeed a relevant technique in practice. Also, we propose an implementation technique which has the same power as the strongest of the previously proposed techniques but requires little or no modification of an existing abstract interpreter.

The role of computational logic as a hinge paradigm among deduction, problem solving, programming, and parallelism

This paper presents some brief considerations on the role of Computational Logic in the construction of Artificial Intelligence systems and in programming in general. It does not address how the many problems in AI can be solved but, rather more modestly, tries to point out some advantages of Computational Logic as a tool for the AI scientist in his quest. It addresses the interaction between declarative and procedural views of programs (deduction and action), the impact of the intrinsic limitations of logic, the relationship with other apparently competing computational paradigms, and finally discusses implementation-related issues, such as the efficiency of current implementations and their capability for efficiently exploiting existing and future sequential and parallel hardware. The purpose of the discussion is in no way to present Computational Logic as the unique overall vehicle for the development of intelligent systems (in the firm belief that such a panacea is yet to be found) but rather to stress its strengths in providing reasonable solutions to several aspects of the task.

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.

Analysis of irregular behaviour on an optical computing logic cell

A new methodology to study irregular behaviours in logic cells is reported. It is based on two types of diagrams, namely phase and working diagrams. Sets of four bits are grouped and represented by their hexadecimal equivalent. Some hexadecimal numbers correspond to certain logic functions. The influence of the internal and external tolerances, namely those appearing in the employed devices and in the working signals, may be analysed with this method. Its importance in the case of logic structures with chaotic behaviours is studied.

Parallel execution of Prolog programs: a survey

Since the early days of logic programming, researchers in the field realized the potential for exploitation of parallelism present in the execution of logic programs. Their high-level nature, the presence of nondeterminism, and their referential transparency, among other characteristics, make logic programs interesting candidates for obtaining speedups through parallel execution. At the same time, the fact that the typical applications of logic programming frequently involve irregular computations, make heavy use of dynamic data structures with logical variables, and involve search and speculation, makes the techniques used in the corresponding parallelizing compilers and run-time systems potentially interesting even outside the field. The objective of this article is to provide a comprehensive survey of the issues arising in parallel execution of logic programming languages along with the most relevant approaches explored to date in the field. Focus is mostly given to the challenges emerging from the parallel execution of Prolog programs. The article describes the major techniques used for shared memory implementation of Or-parallelism, And-parallelism, and combinations of the two. We also explore some related issues, such as memory management, compile-time analysis, and execution visualization.