Implementing distributed concurrent constraint execution in the CIAO system

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

The CIAO Multi-Dialect Compiler and System: An Experimentation Workbench for Future (C)LP Systems

CIAO is an advanced programming environment supporting Logic and Constraint programming. It offers a simple concurrent kernel on top of which declarative and non-declarative extensions are added via librarles. Librarles are available for supporting the ISOProlog standard, several constraint domains, functional and higher order programming, concurrent and distributed programming, internet programming, and others. The source language allows declaring properties of predicates via assertions, including types and modes. Such properties are checked at compile-time or at run-time. The compiler and system architecture are designed to natively support modular global analysis, with the two objectives of proving properties in assertions and performing program optimizations, including transparently exploiting parallelism in programs. The purpose of this paper is to report on recent progress made in the context of the CIAO system, with special emphasis on the capabilities of the compiler, the techniques used for supporting such capabilities, and the results in the áreas of program analysis and transformation already obtained with the system

The CIAO multi-dialect compiler and system: A demo and status report

Abstract is not availabl

Minimizing the overheads of dependent {AND}-parallelism

Parallel implementations of programming languages need to control synchronization overheads. Synchronization is essential for ensuring the correctness of parallel code, yet it adds overheads that aren\u27t present in sequential programs. This is an important problem for parallel logic programming systems, because almost every action in such programs requires accessing variables, and the traditional approach of adding synchronization code to all such accesses is so prohibitively expensive that a parallel version of the program may run more slowly on four processors than a sequential version would run on one processor. We present a program transformation for implementing dependent AND-parallelism in logic programming languages that uses mode information to add synchronization code only to the variable accesses that actually need it

Concurrency in prolog using threads and a shared database

Concurrency in Logic Programming has received much attention in the past. One problem with many proposals, when applied to Prolog, is that they involve large modifications to the standard implementations, and/or the communication and synchronization facilities provided do not fit as naturally within the language model as we feel is possible. In this paper we propose a new mechanism for implementing synchronization and communication for concurrency, based on atomic accesses to designated facts in the (shared) datábase. We argüe that this model is comparatively easy to implement and harmonizes better than previous proposals within the Prolog control model and standard set of built-ins. We show how in the proposed model it is easy to express classical concurrency algorithms and to subsume other mechanisms such as Linda, variable-based communication, or classical parallelism-oriented primitives. We also report on an implementation of the model and provide performance and resource consumption data

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

Automatic compile-time parallelization of logic programs for restricted, goal-level, independent and-parallelism.

A framework for the automatic parallelization of (constraint) logic programs is proposed and proved correct. Intuitively, the parallelization process replaces conjunctions of literals with parallel expressions. Such expressions trigger at run-time the exploitation of restricted, goal-level, independent and-parallelism. The parallelization process performs two steps. The first one builds a conditional dependency graph (which can be implified using compile-time analysis information), while the second transforms the resulting graph into linear conditional expressions, the parallel expressions of the &-Prolog language. Several heuristic algorithms for the latter ("annotation") process are proposed and proved correct. Algorithms are also given which determine if there is any loss of parallelism in the linearization process with respect to a proposed notion of maximal parallelism. Finally, a system is presented which implements the proposed approach. The performance of the different annotation algorithms is compared experimentally in this system by studying the time spent in parallelization and the effectiveness of the results in terms of speedups

Language Interoperability and Logic Programming Languages

We discuss P#, our implementation of a tool which allows interoperation between a concurrent superset of the Prolog programming language and C#. This enables Prolog to be used as a native implementation language for Microsoft's .NET platform. P# compiles a linear logic extension of Prolog to C# source code. We can thus create C# objects from Prolog and use C#'s graphical, networking and other libraries. P# was developed from a modified port of the Prolog to Java translator, Prolog Cafe. We add language constructs on the Prolog side which allow concurrent Prolog code to be written. We add a primitive predicate which evaluates a Prolog structure on a newly forked thread. Communication between threads is based on the unification of variables contained in such a structure. It is also possible for threads to communicate through a globally accessible table. All of the new features are available to the programmer through new built-in Prolog predicates. We present three case studies. The first is an application which allows several users to modify a database. The users are able to disconnect from the database and to modify their own copies of the data before reconnecting. On reconnecting, conflicts must be resolved. The second is an object-oriented assistant, which allows the user to query the contents of a C# namespace or Java package. The third is a tool which allows a user to interact with a graphical display of the inheritance tree. Finally, we optimize P#'s runtime speed by translating some Prolog predicates into more idiomatic C# code than is produced by a naive port of Prolog Cafe. This is achieved by observing that semi-deterministic predicates (being those which always either fail or succeed with exactly one solution) that only call other semi-deterministic predicates enjoy relatively simple control flow. We make use of the fact that Prolog programs often contain predicates which operate as functions, and that such predicates are usually semi-deterministic