Improving the efficiency of nondeterministic indepemndent and-parallel systems

We present the design and implementation of the and-parallel component of ACE. ACE is a computational model for the full Prolog language that simultaneously exploits both or-parallelism and independent and-parallelism. A high performance implementation of the ACE model has been realized and its performance reported in this paper. We discuss how some of the standard problems which appear when implementing and-parallel systems are solved in ACE. We then propose a number of optimizations aimed at reducing the overheads and the increased memory consumption which occur in such systems when using previously proposed solutions. Finally, we present results from an implementation of ACE which includes the optimizations proposed. The results show that ACE exploits and-parallelism with high efficiency and high speedups. Furthermore, they also show that the proposed optimizations, which are applicable to many other and-parallel systems, significantly decrease memory consumption and increase speedups and absolute performance both in forwards execution and during backtracking.

ACE: And/or-parallel copying-based execution of logic programs

In this paper we present a novel execution model for parallel implementation of logic programs which is capable of exploiting both independent and-parallelism and or-parallelism in an efficient way. This model extends the stack copying approach, which has been successfully applied in the Muse system to implement or-parallelism, by integrating it with proven techniques used to support independent and-parallelism. We show how all solutions to non-deterministic andparallel goals are found without repetitions. This is done through recomputation as in Prolog (and in various and-parallel systems, like &-Prolog and DDAS), i.e., solutions of and-parallel goals are not shared. We propose a scheme for the efficient management of the address space in a way that is compatible with the apparently incompatible requirements of both and- and or-parallelism. We also show how the full Prolog language, with all its extra-logical features, can be supported in our and-or parallel system so that its sequential semantics is preserved. The resulting system retains the advantages of both purely or-parallel systems as well as purely and-parallel systems. The stack copying scheme together with our proposed memory management scheme can also be used to implement models that combine dependent and-parallelism and or-parallelism, such as Andorra and Prometheus.

Divided we stand: Parallel distributed stack memory management

We present an overview of the stack-based memory management techniques that we used in our non-deterministic and-parallel Prolog systems: &-Prolog and DASWAM. We believe that the problems associated with non-deterministic and-parallel systems are more general than those encountered in or-parallel and deterministic and-parallel systems, which can be seen as subsets of this more general case. We develop on the previously proposed "marker scheme", lifting some of the restrictions associated with the selection of goals while keeping (virtual) memory consumption down. We also review some of the other problems associated with the stack-based management scheme, such as handling of forward and backward execution, cut, and roll-backs.

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.

Experimenting with independent and-parallel prolog using standard prolog

This paper presents an approximation to the study of parallel systems using sequential tools. The Independent And-parallelism in Prolog is an example of parallel processing paradigm in the framework of logic programming, and implementations like parallel processing. But this potential can also be explored using only sequential systems. Being the spirit of this paper to show how this can be done with a standard system, only standard Prolog will be used in the implementations included. Such implementations include tests for parallelism in And-Prolog, a correctnesschecking meta-interpreter of parallel execution for

Experimenting with independent and-parallel prolog using standard prolog

This paper presents an approximation to the study of parallel systems using sequential tools. The Independent And-parallelism in Prolog is an example of parallel processing paradigm in the framework of logic programming, and implementations like parallel processing. But this potential can also be explored using only sequential systems. Being the spirit of this paper to show how this can be done with a standard system, only standard Prolog will be used in the implementations included. Such implementations include tests for parallelism in And-Prolog, a correctnesschecking meta-interpreter of parallel execution for

On real-time partitioned multicore systems

Partitioning is a common approach to developing mixed-criticality systems, where partitions are isolated from each other both in the temporal and the spatial domain in order to prevent low-criticality subsystems from compromising other subsystems with high level of criticality in case of misbehaviour. The advent of many-core processors, on the other hand, opens the way to highly parallel systems in which all partitions can be allocated to dedicated processor cores. This trend will simplify processor scheduling, although other issues such as mutual interference in the temporal domain may arise as a consequence of memory and device sharing. The paper describes an architecture for multi-core partitioned systems including critical subsystems built with the Ada Ravenscar profile. Some implementation issues are discussed, and experience on implementing the ORK kernel on the XtratuM partitioning hypervisor is presented.

Memory isolation in many-core embedded systems

The current approach to developing mixed-criticality sys- tems is by partitioning the hardware resources (processors, memory and I/O devices) among the different applications. Partitions are isolated from each other both in the temporal and the spatial domain, so that low-criticality applications cannot compromise other applications with a higher level of criticality in case of misbehaviour. New architectures based on many-core processors open the way to highly parallel systems in which each partition can be allocated to a set of dedicated proces- sor cores, thus simplifying partition scheduling and temporal separation. Moreover, spatial isolation can also benefit from many-core architectures, by using simpler hardware mechanisms to protect the address spaces of different applications. This paper describes an architecture for many- core embedded partitioned systems, together with some implementation advice for spatial isolation.

IDRA (IDeal Resource Allocation): A tool for computing ideal speedups

Performance studies of actual parallel systems usually tend to concéntrate on the effectiveness of a given implementation. This is often done in the absolute, without quantitave reference to the potential parallelism contained in the programs from the point of view of the execution paradigm. We feel that studying the parallelism inherent to the programs is interesting, as it gives information about the best possible behavior of any implementation and thus allows contrasting the results obtained. We propose a method for obtaining ideal speedups for programs through a combination of sequential or parallel execution and simulation, and the algorithms that allow implementing the method. Our approach is novel and, we argüe, more accurate than previously proposed methods, in that a crucial part of the data - the execution times of tasks - is obtained from actual executions, while speedup is computed by simulation. This allows obtaining speedup (and other) data under controlled and ideal assumptions regarding issues such as number of processor, scheduling algorithm and overheads, etc. The results obtained can be used for example to evalúate the ideal parallelism that a program contains for a given model of execution and to compare such "perfect" parallelism to that obtained by a given implementation of that model. We also present a tool, IDRA, which implements the proposed method, and results obtained with IDRA for benchmark programs, which are then compared with those obtained in actual executions on real parallel systems.

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.

Using attributed variables in the implementation of concurrent and parallel logic programming systems

Incorporating the possibility of attaching attributes to variables in a logic programming system has been shown to allow the addition of general constraint solving capabilities to it. This approach is very attractive in that by adding a few primitives any logic programming system can be turned into a generic constraint logic programming system in which constraint solving can be user deñned, and at source level - an extreme example of the "glass box" approach. In this paper we propose a different and novel use for the concept of attributed variables: developing a generic parallel/concurrent (constraint) logic programming system, using the same "glass box" flavor. We argüe that a system which implements attributed variables and a few additional primitives can be easily customized at source level to implement many of the languages and execution models of parallelism and concurrency currently proposed, in both shared memory and distributed systems. We illustrate this through examples and report on an implementation of our ideas.

On the uses of attributed variables in parallel and concurrent logic programming systems

Incorporating the possibility of attaching attributes to variables in a logic programming system has been shown to allow the addition of general constraint solving capabilities to it. This approach is very attractive in that by adding a few primitives any logic programming system can be turned into a generic constraint logic programming system in which constraint solving can be user defined, and at source level - an extreme example of the "glass box" approach. In this paper we propose a different and novel use for the concept of attributed variables: developing a generic parallel/concurrent (constraint) logic programming system, using the same "glass box" flavor. We argüe that a system which implements attributed variables and a few additional primitives can be easily customized at source level to implement many of the languages and execution models of parallelism and concurrency currently proposed, in both shared memory and distributed systems. We illustrate this through examples.

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.

Distributed models in P-Systems architectures to reduce computation time

Membrane systems are computational equivalent to Turing machines. However, their distributed and massively parallel nature obtains polynomial solutions opposite to traditional non-polynomial ones. At this point, it is very important to develop dedicated hardware and software implementations exploiting those two membrane systems features. Dealing with distributed implementations of P systems, the bottleneck communication problem has arisen. When the number of membranes grows up, the network gets congested. The purpose of distributed architectures is to reach a compromise between the massively parallel character of the system and the needed evolution step time to transit from one configuration of the system to the next one, solving the bottleneck communication problem. The goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the main results regarding the way membranes can be placed on processors in order to get a software/hardware simulation of P-Systems in a distributed environment. Secondly, we improve some results about the membrane dissolution problem, prove that it is connected, and discuss the possibility of simulating this property in the distributed model. All this yields an improvement in the system parallelism implementation since it gets an increment of the parallelism of the external communication among processors. Proposed ideas improve previous architectures to tackle the communication bottleneck problem, such as reduction of the total time of an evolution step, increase of the number of membranes that could run on a processor and reduction of the number of processors.

Exploiting Structured Linked Data in Enterprise Knowledge Management Systems: An Idea Management Case Study

In parallel to the effort of creating Open Linked Data for the World Wide Web there is a number of projects aimed for developing the same technologies but in the context of their usage in closed environments such as private enterprises. In the paper, we present results of research on interlinking structured data for use in Idea Management Systems - a still rare breed of knowledge management systems dedicated to innovation management. In our study, we show the process of extending an ontology that initially covers only the Idea Management System structure towards the concept of linking with distributed enterprise data and public data using Semantic Web technologies. Furthermore we point out how the established links can help to solve the key problems of contemporary Idea Management Systems