The Constraint Logic Programming Scheme defines a class of languages designed for programming with constraints using a logic programming approach. These languages are soundly based on a unified framework of formal semantics. In particular, as an instance of this scheme with real arithmetic constraints, the CLP(R) language facilitates and encourages a concise and declarative style of programming for problems involving a mix of numeric and non-numeric computation. In this paper we illustrate the practical applicability of CLP(R) with examples of programs to solve electrical engineering problems. This field is particularly rich in problems that are complex and largely numeric, enabling us to demonstrate a number of the unique features of CLP(R). A detailed look at some of the more important programming techniques highlights the ability of CLP(R) to support well-known, powerful techniques from constraint programming. Our thesis is that CLP(R) is an embodiment of these techniques in a langu...

We develop a new computational model for representing the fine-grained meanings of near-synonyms and the differences between them. We also develop a sophisticated lexical-choice process that can decide which of several near-synonyms is most appropriate in a particular situation. This research has direct applications in machine translation and text generation. We first identify the problems of representing near-synonyms in a computational lexicon and show that no previous model adequately accounts for near-synonymy. We then propose a preliminary theory to account for near-synonymy, relying crucially on the notion of granularity of representation, in which the meaning of a word arises out of a context-dependent combination of a context-independent core meaning and a set of explicit differences to its near-synonyms. That is, near-synonyms cluster together. We then develop a clustered model of lexical knowledge, derived from the conventional ontological model. The model cuts off the ontology at a coarse grain, thus avoiding an awkward proliferation of language-dependent concepts in the ontology, and groups near-synonyms into subconceptual clusters that are linked to the ontology. A cluster differentiates near-synonyms in terms of fine-grained aspects of denotation, implication, expressed attitude, and style. The model is general enough to account for other types of variation, for instance, in collocational behaviour. An efficient, robust, and flexible fine-grained lexical-choice process is a consequence of a clustered model of lexical knowledge. To make it work, we formalize criteria for lexical choice as preferences to express certain concepts with varying indirectness, to express attitudes, and to establish certain styles. The lexical-choice process itself works on two tiers: between clusters and between near-synonyns of clusters. We describe our prototype implementation of the system, called I-Saurus.

The data-parallel language High Performance Fortran (HPF) does not allow efficient expression of mixed task/data-parallel computations or the coupling of separately compiled data-parallel modules. In this paper, we show how these common parallel program structures can be represented, with only minor extensions to the HPF model, by using a coordination library based on the Message Passing Interface (MPI). This library allows data-parallel tasks to exchange distributed data structures using calls to simple communication functions. We present microbenchmark results that characterize the performance of this library and that quantify the impact of optimizations that allow reuse of communication schedules in common situations. In addition, results from two-dimensional FFT, convolution, and multiblock programs demonstrate that the HPF/MPI library can provide performance superior to that of pure HPF. We conclude that this synergistic combination of two parallel programming standards represents...

Choosing the wrong word in a machine translation or natural language generation system can convey unwanted connotations, implications, or attitudes. The choice between near-synonyms such as error, mistake, slip, and blunder — words that share the same core meaning, but differ in their nuances — can be made only if knowledge about their differences is available. We present a method to automatically acquire a new type of lexical resource: a knowledgebase of near-synonym differences. We develop an unsupervised decision-list algorithm that learns extraction patterns from a special dictionary of synonym differences. The patterns are then used to extract knowledge from the text of the dictionary. The initial knowledge-base is later enriched with information from other machine-readable dictionaries. Information about the collocational behavior of the near-synonyms is acquired from free text. The knowledge-base is used by Xenon, a natural language generation system that shows how the new lexical resource can be used to choose the best near-synonym in specific situations. 1. Near-synonyms Near-synonyms are words that are almost synonyms, but not quite. They are not fully inter-substitutable, but vary in their shades of denotation or connotation, or in the components

Data-parallel languages such as High Performance Fortran (HPF) present a simple execution model in which a single thread of control performs high-level operations on distributed arrays. These languages can greatly ease the development of parallel programs. Yet there are large classes of applications for which a mixture of task and data parallelism is most appropriate. Such applications can be structured as collections of data-parallel tasks that communicate by using explicit message passing. Because the Message Passing Interface (MPI) defines standardized, familiar mechanisms for this communication model, we propose that HPF tasks communicate by making calls to a coordination library that provides an HPF binding for MPI. The semantics of a communication interface for sequential languages can be ambiguous when the interface is invoked from a parallel language; we show how these ambiguities can be resolved by describing one possible HPF binding for MPI. We then present the design of a li...

Data-parallel programming languages can reduce the difficulty of developing efficient applications for contemporary parallel computers. However, many applications can benefit from a mixture of task and data parallelism. We present a library-based approach that permits programmers to coordinate data-parallel tasks using explicit message-passing operations. We discuss in detail the design of a prototype library that supports inter-task transfers of arrays in an efficient manner on distributed-memory multicomputers. Measurements with a synthetic benchmark show that in many cases the library can realize a significant fraction of a multicomputer 's peak communication performance, and reveal the sources of overheads that reduce the library's performance in other cases. We also develop an analytic model of array transfer performance as a means of predicting inter-task communication costs. iii For Jingjun, for pushing me to finish iv Acknowledgments First of all, I thank my supervisor at A...

Persistent programming has many facets ranging from simple variables outliving a specific program to persistent single-level stores generalizing the idea of memory. Therefore we are concerned in the means, how different semantics of persistent objects can be implemented as well as expressed and controlled. Configurability of the underlying system becomes an important issue then, especially when focusing on runtime-efficiency. In this paper we are discussing different approaches to persistence and see how they apply to the domain of parallel computation. Finally we propose a flexible framework for persistent programming, which is based on the notion of persistent heaps. 1 Introduction The fundamental property of persistent programming is the introduction of language-level objects, which are able to outlive the program, that created them. This feature essentially refrains the burden from the programmer of caring about different data storage formats for volatile and non volatil...

Much research has been conducted on the formulation of inheritance in object-orientedness. Most proposals retain the semantic relationship between the superclass and subclass, but deliberately ignore the issues of overriding, which plays an important role in object-oriented modelling. Others use class inheritance and module inheritance to distinguish between the cases of inheritance with and without overriding, but, as a result, one fundamental concept is partitioned into two. Some research supports overriding, but not transitivity. This thesis addresses the issue of overriding in object-orientedness, illustrates how a single inheritance concept can be formalized using Communicating Sequential Processes (CSP), proposes a refined concept of conformance which is transitive, and demonstrates the practical application of our theory. This project compares favourably with other related work. In this thesis, we identify that reflexivity, anti-symmetry, transitivity, overriding, behavioural compatibility, formality, incrementality and multiple inheritance are the desirable features of a theory of inheritance. We formalize the concept of behavioural inheritance as a special kind of conformance relation that links a subclass to its superclass by the Fidge’s priority choice operator. Using the priority choice operator, we integrate naturally the concept of overriding into our formalization and provide a support for an incremental development. Transitivity is realized by the introduction of strong conformance which can be used as a unification of extension and reduction. It also provides a framework of reflexivity and anti-symmetry for the inheritance relation. Through strong conformance, behaviour compatibilities between the superclasses and subclasses can be ensured. We also refine our theory to support multiple inheritance and propose a method to resolve ambiguity raised by multiple inheritance. Finally, a criteria for generating an optimal incremental change will be presented.

) of any n-dimensional lattice, and to calculate the covering multiplicities of various well-known lattices. Figure 1 shows an example. The covering multiplicity so defined is of use in estimating various integrals, since if I is the integral of some function over the whole space and I B its integral over one of the covering balls then I B S I B CM(L) I . __________________________________ The figures appear at the end of the paper __________________________________ In the present paper we determine the covering multiplicities of certain members of the families I n (n ³ 1), A n (n ³ 1), D n (n ³ 1), E n (n = 6 , 7 , 8) and their duals A n * , D n * , E n * for small values of n (the results are given in Table I) and of the Leech lattice L 24 (for which the covering multiplicity is 25). Table I Covering multiplicities of root lattices and duals _____________________________________________________ n I n A n A n * D n D n * E n E n * ______________________________...