Non-failure analysis for logic programs

We provide a method whereby, given mode and (upper approximation) type information, we can detect procedures and goals that can be guaranteed to not fail (i.e., to produce at least one solution or not termínate). The technique is based on an intuitively very simple notion, that of a (set of) tests "covering" the type of a set of variables. We show that the problem of determining a covering is undecidable in general, and give decidability and complexity results for the Herbrand and linear arithmetic constraint systems. We give sound algorithms for determining covering that are precise and efiicient in practice. Based on this information, we show how to identify goals and procedures that can be guaranteed to not fail at runtime. Applications of such non-failure information include programming error detection, program transiormations and parallel execution optimization, avoiding speculative parallelism and estimating lower bounds on the computational costs of goals, which can be used for granularity control. Finally, we report on an implementation of our method and show that better results are obtained than with previously proposed approaches.

Optimized algorithms for the incremental analysis of logic programs

Global analysis of logic programs can be performed effectively by the use of one of several existing efficient algorithms. However, the traditional global analysis scheme in which all the program code is known in advance and no previous analysis information is available is unsatisfactory in many situations. Incrementa! analysis of logic programs has been shown to be feasible and much more efficient in certain contexts than traditional (non-incremental) global analysis. However, incremental analysis poses additional requirements on the fixpoint algorithm used. In this work we identify these requirements, present an important class of strategies meeting the requirements, present sufficient a priori conditions for such strategies, and propose, implement, and evalúate experimentally a novel algorithm for incremental analysis based on these ideas. The experimental results show that the proposed algorithm performs very efficiently in the incremental case while being comparable to (and, in some cases, considerably better than) other state-of-the-art analysis algorithms even for the non-incremental case. We argüe that our discussions, results, and experiments also shed light on some of the many tradeoffs involved in the design of algorithms for logic program analysis.

IDRA (IDeal Resource Allocation): Computing ideal speedups in parallel logic programming

We present a technique to estimate accurate speedups for parallel logic programs with relative independence from characteristics of a given implementation or underlying parallel hardware. The proposed technique is based on gathering accurate data describing one execution at run-time, which is fed to a simulator. Alternative schedulings are then simulated and estimates computed for the corresponding speedups. A tool implementing the aforementioned techniques is presented, and its predictions are compared to the performance of real systems, showing good correlation.

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.

Effectiveness of global analysis in strict independence-based automatic program parallelization

This paper presents a study of the effectiveness of global analysis in the parallelization of logic programs using strict independence. A number of well-known approximation domains are selected and tlieir usefulness for the application in hand is explained. Also, methods for using the information provided by such domains to improve parallelization are proposed. Local and global analyses are built using these domains and such analyses are embedded in a complete parallelizing compiler. Then, the performance of the domains (and the system in general) is assessed for this application through a number of experiments. We argüe that the results offer significant insight into the characteristics of these domains, the demands of the application, and the tradeoffs involved.

A comparative study of methods for automatic compile-time parallelization of logic programs

This paper presents a study of the effectiveness of three different algorithms for the parallelization of logic programs based on compile-time detection of independence among goals. The algorithms are embedded in a complete parallelizing compiler, which incorporates different abstract interpretation-based program analyses. The complete system shows the task of automatic program parallelization to be practical. The trade-offs involved in using each of the algorithms in this task are studied experimentally, weaknesses of these identified, and possible improvements discussed.

Some paradigms for visualizing parallel execution of logic programs

This paper addresses the design of visual paradigms for observing the parallel execution of logic programs. First, an intuitive method is proposed for arriving at the design of a paradigm and its implementation as a tool for a given model of parallelism. This method is based on stepwise reñnement starting from the deñnition of basic notions such as events and observables and some precedence relationships among events which hold for the given model of parallelism. The method is then applied to several types of parallel execution models for logic programs (Orparallelism, Determinate Dependent And parallelism, Restricted and-parallelism) for which visualization paradigms are designed. Finally, VisAndOr, a tool which implements all of these paradigms is presented, together with a discussion of its usefulness through examples.

The CDG, UDG, and MEL methods for automatic compile-time parallelization of logic programs for independent and-parallelism

There has been significant interest in parallel execution models for logic programs which exploit Independent And-Parallelism (IAP). In these models, it is necessary to determine which goals are independent and therefore eligible for parallel execution and which goals have to wait for which others during execution. Although this can be done at run-time, it can imply a very heavy overhead. In this paper, we present three algorithms for automatic compiletime parallelization of logic programs using IAP. This is done by converting a clause into a graph-based computational form and then transforming this graph into linear expressions based on &-Prolog, a language for IAP. We also present an algorithm which, given a clause, determines if there is any loss of parallelism due to linearization, for the case in which only unconditional parallelism is desired. Finally, the performance of these annotation algorithms is discussed for some benchmark programs.

On the practicality of global flow analysis of logic programs

This paper addresses the issue of the practicality of global flow analysis in logic program compilation, in terms of both speed and precision of analysis. It discusses design and implementation aspects of two practical abstract interpretation-based flow analysis systems: MA3, the MOO Andparallel Analyzer and Annotator; and Ms, an experimental mode inference system developed for SB-Prolog. The paper also provides performance data obtained from these implementations. Based on these results, it is concluded that the overhead of global flow analysis is not prohibitive, while the results of analysis can be quite precise and useful.

Relating goal scheduling, precedence, and memory management in and-parallel execution of logic programs

The interactions among three important issues involved in the implementation of logic programs in parallel (goal scheduling, precedence, and memory management) are discussed. A simplified, parallel memory management model and an efficient, load-balancing goal scheduling strategy are presented. It is shown how, for systems which support "don't know" non-determinism, special care has to be taken during goal scheduling if the space recovery characteristics of sequential systems are to be preserved. A solution based on selecting only "newer" goals for execution is described, and an algorithm is proposed for efficiently maintaining and determining precedence relationships and variable ages across parallel goals. It is argued that the proposed schemes and algorithms make it possible to extend the storage performance of sequential systems to parallel execution without the considerable overhead previously associated with it. The results are applicable to a wide class of parallel and coroutining systems, and they represent an efficient alternative to "all heap" or "spaghetti stack" allocation models.

B-LOG: A branch and bound methodology for the parallel execution of logic programs

We propose a computational methodology -"B-LOG"-, which offers the potential for an effective implementation of Logic Programming in a parallel computer. We also propose a weighting scheme to guide the search process through the graph and we apply the concepts of parallel "branch and bound" algorithms in order to perform a "best-first" search using an information theoretic bound. The concept of "session" is used to speed up the search process in a succession of similar queries. Within a session, we strongly modify the bounds in a local database, while bounds kept in a global database are weakly modified to provide a better initial condition for other sessions. We also propose an implementation scheme based on a database machine using "semantic paging", and the "B-LOG processor" based on a scoreboard driven controller.

Abstract Interpretation-based verification/certification in the ciaoPP system

CiaoPP is the abstract interpretation-based preprocessor of the Ciao multi-paradigm (Constraint) Logic Programming system. It uses modular, incremental abstract interpretation as a fundamental tool to obtain information about programs. In CiaoPP, the semantic approximations thus produced have been applied to perform high- and low-level optimizations during program compilation, including transformations such as múltiple abstract specialization, parallelization, partial evaluation, resource usage control, and program verification. More recently, novel and promising applications of such semantic approximations are being applied in the more general context of program development such as program verification. In this work, we describe our extensión of the system to incorpórate Abstraction-Carrying Code (ACC), a novel approach to mobile code safety. ACC follows the standard strategy of associating safety certificates to programs, originally proposed in Proof Carrying- Code. A distinguishing feature of ACC is that we use an abstraction (or abstract model) of the program computed by standard static analyzers as a certifícate. The validity of the abstraction on the consumer side is checked in a single-pass by a very efficient and specialized abstractinterpreter. We have implemented and benchmarked ACC within CiaoPP. The experimental results show that the checking phase is indeed faster than the proof generation phase, and that the sizes of certificates are reasonable. Moreover, the preprocessor is based on compile-time (and run-time) tools for the certification of CLP programs with resource consumption assurances.

A program transformation for continuation call-based tabled execution

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 suspensión) require. This implementation effort is reduced by program transformation-based continuation cali techniques, at some eñrciency 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 cali 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.

Towards execution time estimation for logic programs via static analysis and profiling

Effective static analyses have been proposed which infer bounds on the number of resolutions or reductions. These have the advantage of being independent from the platform on which the programs are executed and have been shown to be useful in a number of applications, such as granularity control in parallel execution. On the other hand, in distributed computation scenarios where platforms with different capabilities come into play, it is necessary 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 times. With this objective in mind, we propose an approach which combines compile-time analysis for cost bounds with a one-time profiling of the platform in order to determine the valúes of certain parameters for a given platform. These parameters calíbrate 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 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.