Towards a High-Level Implementation of Execution Primitives for Unrestricted, Independent And-Parallelism

Most efficient implementations of parallel logic programming rely on complex low-level machinery which is arguably difficult to implement and modify. We explore an alternative approach aimed at taming that complexity by raising core parts of the implementation to the source language level for the particular case of and-parallellism. We handle a significant portion of the parallel implementation at the Prolog level with the help of a comparatively small number of concurrency.related primitives which take case of lower-level tasks such as locking, thread management, stack set management, etc. The approach does not eliminate altogether modifications to the abstract machine, but it does greatly simplify them and it also facilitates experimenting with different alternatives. We show how this approach allows implementing both restricted and unrestricted (i.e., non fork-join) parallelism. Preliminary esperiments show thay the performance safcrifieced is reasonable, although granularity of unrestricted parallelism contributes to better observed speedups

Towards high-level execution primitives for and-parallelism: preliminary results

Most implementations of parallel logic programming rely on complex low-level machinery which is arguably difflcult to implement and modify. We explore an alternative approach aimed at taming that complexity by raising core parts of the implementation to the source language level for the particular case of and-parallelism. Therefore, we handle a signiflcant portion of the parallel implementation mechanism at the Prolog level with the help of a comparatively small number of concurrency-related primitives which take care of lower-level tasks such as locking, thread management, stack set management, etc. The approach does not eliminate altogether modiflcations to the abstract machine, but it does greatly simplify them and it also facilitates experimenting with different alternatives. We show how this approach allows implementing both restricted and unrestricted (i.e., non fork-join) parallelism. Preliminary experiments show that the amount of performance sacriflced is reasonable, although granularity control is required in some cases. Also, we observe that the availability of unrestricted parallelism contributes to better observed speedups

Logic Programming: Context, Character and Development

Logic programming has been attracting increasing interest in recent years. Its first realisation in the form of PROLOG demonstrated concretely that Kowalski's view of computation as controlled deduction could be implemented with tolerable efficiency, even on existing computer architectures. Since that time logic programming research has intensified. The majority of computing professionals have remained unaware of the developments, however, and for some the announcement that PROLOG had been selected as the core language for the Japanese 'Fifth Generation' project came as a total surprise. This thesis aims to describe the context, character and development of logic programming. It explains why a radical departure from existing software practices needs to be seriously discussed; it identifies the characteristic features of logic programming, and the practical realisation of these features in current logic programming systems; and it outlines the programming methodology which is proposed for logic programming. The problems and limitations of existing logic programming systems are described and some proposals for development are discussed. The thesis is in three parts. Part One traces the development of programming since the early days of computing. It shows how the problems of software complexity which were addressed by the 'structured programming' school have not been overcome: the software crisis remains severe and seems to require fundamental changes in software practice for its solution. Part Two describes the foundations of logic programming in the procedural interpretation of Horn clauses. Fundamental to logic programming is shown to be the separation of the logic of an algorithm from its control. At present, however, both the logic and the control aspects of logic programming present problems; the first in terms of the extent of the language which is used, and the second in terms of the control strategy which should be applied in order to produce solutions. These problems are described and various proposals, including some which have been incorporated into implemented systems, are described. Part Three discusses the software development methodology which is proposed for logic programming. Some of the experience of practical applications is related. Logic programming is considered in the aspects of its potential for parallel execution and in its relationship to functional programming, and some possible criticisms of the problem-solving potential of logic are described. The conclusion is that although logic programming inevitably has some problems which are yet to be solved, it seems to offer answers to several issues which are at the heart of the software crisis. The potential contribution of logic programming towards the development of software should be substantial

Why a Single Parallelization Strategy Is Not Enough in Knowledge Bases

We address the problem of parallelizing the evaluation of logic programs in data intensive applications. We argue that the appropriate parallelization strategy for logic-program evaluation depends on the program being evaluated. Therefore, this paper is concerned with the issues of program classification and parallelization strategies. We propose several parallelization strategies based on the concept of data reduction—the original logic program is evaluated by several processors working in parallel, each using only a subset of the database. The strategies differ on the evaluation cost, the overhead of communication and synchronization among processors, and the programs to which they are applicable. In particular, we start our study with pure parallelization, i.e., parallelization without overhead. An interesting class structure of logic programs is demonstrated, when considering amenability to pure parallelization. The relationship to the NC complexity class is demonstrated. Then we propose strategies that do incur an overhead, but are optimal in a sense that will be precisely defined. This paper makes the initial steps towards a theory of parallel logic programming

Restoration of legacy parallelism in C and C++ applications

Parallel patterns are a high-level programming paradigm that enables non-experts in parallelism to develop structured parallel programs that are maintainable, adaptive, and portable whilst achieving good performance on a variety of parallel systems. However, there still exists a large base of legacy-parallel code developed using ad-hoc methods and incorporating low-level parallel/concurrency libraries such as pthreads without any parallel patterns in the fundamental design. This code would benefit from being restructured and rewritten into pattern-based code. However, the process of rewriting the code is laborious and error-prone, due to typical concurrency and pthreading code being closely intertwined throughout the business logic of the program. In this paper, we present a new software restoration methodology, to transform legacy-parallel programs implemented using e.g. pthreads into structured patterned equivalents. We demonstrate our restoration technique on a number of benchmarks, allowing the introduction of patterned parallelism in the resulting code; we record improvements in cyclomatic complexity and speedups.PostprintPeer reviewe

Extensible sparse functional arrays with circuit parallelism

A longstanding open question in algorithms and data structures is the time and space complexity of pure functional arrays. Imperative arrays provide update and lookup operations that require constant time in the RAM theoretical model, but it is conjectured that there does not exist a RAM algorithm that achieves the same complexity for functional arrays, unless restrictions are placed on the operations. The main result of this paper is an algorithm that does achieve optimal unit time and space complexity for update and lookup on functional arrays. This algorithm does not run on a RAM, but instead it exploits the massive parallelism inherent in digital circuits. The algorithm also provides unit time operations that support storage management, as well as sparse and extensible arrays. The main idea behind the algorithm is to replace a RAM memory by a tree circuit that is more powerful than the RAM yet has the same asymptotic complexity in time (gate delays) and size (number of components). The algorithm uses an array representation that allows elements to be shared between many arrays with only a small constant factor penalty in space and time. This system exemplifies circuit parallelism, which exploits very large numbers of transistors per chip in order to speed up key algorithms. Extensible Sparse Functional Arrays (ESFA) can be used with both functional and imperative programming languages. The system comprises a set of algorithms and a circuit specification, and it has been implemented on a GPGPU with good performance

Lower-bound Time-Complexity Analysis of Logic Programs

The paper proposes a technique for inferring conditions on goals that, when satisfied, ensure that a goal is sufficiently coarse-grained to warrant parallel evaluation. The method is powerful enough to reason about divide-and-conquer programs, and in the case of quicksort, for instance, can infer that a quicksort goal has a time complexity that exceeds 64 resolution steps (a threshold for spawning) if the input list is of length 10 or more. This gives a simple run-time tactic for controlling spawning. The method has been proved correct, can be implemented straightforwardly, has been demonstrated to be useful on a parallel machine, and, in contrast with much of the previous work on time-complexity analysis of logic programs, does not require any complicated difference equation solving machinery

BSF-skeleton: A Template for Parallelization of Iterative Numerical Algorithms on Cluster Computing Systems

This article describes a method for creating applications for cluster computing systems using the parallel BSF skeleton based on the original BSF (Bulk Synchronous Farm) model of parallel computations developed by the author earlier. This model uses the master/slave paradigm. The main advantage of the BSF model is that it allows to estimate the scalability of a parallel algorithm before its implementation. Another important feature of the BSF model is the representation of problem data in the form of lists that greatly simplifies the logic of building applications. The BSF skeleton is designed for creating parallel programs in C++ using the MPI library. The scope of the BSF skeleton is iterative numerical algorithms of high computational complexity. The BSF skeleton has the following distinctive features. - The BSF-skeleton completely encapsulates all aspects that are associated with parallelizing a program. - The BSF skeleton allows error-free compilation at all stages of application development. - The BSF skeleton supports OpenMP programming model and workflows.Comment: Submitted to Methods