This paper gives some examples of how computation in a number of languages may be described as graph rewriting, giving the Dactl notation for the examples shown. It goes on to present the Dactl model more formally before giving a formal definition of the syntax and semantics of the language. 2 Examples of Computation by Graph Rewriting

Data-parallel ML is proposed for compilation to a distributed version (DPCAM) of Cousineau, Curien and Mauny's Categorical Abstract Machine. The DPCAM is a static network of CAMs which dynamically restrict the MIMD execution mode: nodes execute the same program and communicate only while executing the same function body. Programs violating this restriction or exhibiting unbounded spatial recursion abort or deadlock. The execution model thus defines a class of SPMD programs. With respect to syntax and types, DPML is Mini-ML enriched with localization and remote evaluation functions. Its values are arrays of size matching the DPCAM network and containing ML values. Pointwise functions, data-parallel primitives and systolic algorithms are easily programmed. To improve the lang...

The increasing availability of commodity multicore processors is making parallel computing available to the masses. Traditional parallel languages are largely intended for large-scale scientific computing and tend not to be well-suited to programming the applications one typically finds on a desktop system. Thus we need new parallel-language designs that address a broader spectrum of applications. In this paper, we present Manticore, a language for building parallel applications on commodity multicore hardware including a diverse collection of parallel constructs for different granularities of work. We focus on the implicitly-threaded parallel constructs in our high-level functional language. We concentrate on those elements that distinguish our design from related ones, namely, a novel parallel binding form, a nondeterministic parallel case form, and exceptions in the presence of data parallelism. These features differentiate the present work from related work on functional data parallel language designs, which has focused largely on parallel problems with regular structure and the compiler transformations — most notably, flattening — that make such designs feasible. We describe our implementation strategies and present some detailed examples utilizing various mechanisms of our language.

The generalised term graph rewriting computational model is exploited to implement concurrent languages based on Girard's Linear Logic (LL). In particular a fragment of LL is identified which is able to serve as a "process calculus" and on which the design of a number of languages can be based. It is then shown how this fragment can be mapped onto equivalent sets of graph rewriting rules that both preserve the functionality of the LL connectives and also exploit the properties of linearity for efficient implementation on a distributed architecture. Notions such as channels, production and consumption of messages, and N-to-N communication between agents, are interpreted in the world of (term) graph rewriting. This work serves two purposes: i) to extend the notion of Term Graph Rewriting as a generalised computational model for the case of linear concurrent languages, and ii) to act as an initial investigation towards a fully linear term graph rewriting model of computation able to be im...

In this thesis we address the challenges associated with the provision of dynamic software architectures. These are systems in which programs are constructed from separately compiled units with a facility for the replacement of these units at runtime. Typical examples of applications which will benefit from this dynamic approach are long-lived systems in which downtime is highly undesirable, for example, web-servers, database engines, and equipment controllers. In addition, dynamic software architectures are also gaining popularity with the recent advent of wide-area Internet applications, where it is often impractical to compile a program in its entirety or begin execution in a single step. Our approach to dynamic software architectures differs from earlier attempts in that we guarantee the safety of the replacement operation. This is done by founding our techniques on the rigour of strong typing. In the first half of the thesis we take an existing static software architecture with strong typing facilities and modular program construction, namely the Standard ML platform, and equip

Two of the currently most promising programming paradigms, namely Object-Oriented Programming and Concurrent Constraint Programming are combined into a single, highly parallel computational model based on Term Graph Rewriting Systems. In particular, we show how multi-headed Term Graph rewrite rules provide a powerful tool able to manipulate Term Graphs which themselves represent in a homogeneous way objects, concurrently executing agents and constraints. Due to the inherent fine grain parallelism of Term Graph Rewriting the proposed model is highly parallel with all activities (object communication, agent execution and constraint solving) executing concurrently. 1. Introduction The generalised computational model of Term Graph Rewriting Systems (TGRS) ([5]) has been used extensively as an implementation vehicle for a number of, often divergent, programming paradigms ranging from the traditional functional programming ones ([12,15]) to the (concurrent) logic programming ones ([3,10,18])...

The relationship between the generalised computational model of Term Graph Rewriting Systems (TGRS) and Object-Oriented Programming (OOP) is explored and exploited by extending the TGRS model with records where access to parameters is done by naming rather than position. Records are then used as the basis for expressing object-oriented techniques such as object encapsulation and (various forms of) inheritance. The effect is that TGRS with records can now be used as an implementation model for a variety of (concurrent) object-oriented (functional, logic or otherwise) languages but also as a common formalism for comparing various related techniques (such as different forms of inheritance or approaches for providing solutions to problems caused by the combination of concurrency and interaction between objects). Keywords: Object-Oriented Programming; Concurency and Parallelism; Programming Language Extensions; Rewriting Systems. Object-Oriented Term Graph Rewriting George A. Papadopoulos...

Efficient type inference algorithms are based on graph-rewriting techniques. Consequently, at first sight they seem unsuitable for functional language implementation. In fact, most compilers written in functional languages use substitution-based algorithms, at a considerable cost in performance. In this paper, we show how monads may be used to transform a substitution-based inference algorithm into one using a graph representation. The resulting algorithm is faster than the corresponding substitutionbased algorithm. Monads are also used to develop a parallel substitution inference algorithm. Practical considerations limit the development of a parallel graph-rewriting algorithm in a functional language. 1 Introduction Type inference accounts for much of the cost of compiling a functional program. Typically around half of the total space and time requirements of a compilation in the Glasgow prototype Haskell compiler, or the Chalmers LML compiler can be attributed directly to the costs o...

this paper we try to bridge the gap between the two formalisms by showing how concurrent logic languages can be implemented using graph rewriting. In particular, we develop techniques for mapping a wide class of CLLs including Parlog, GHC, Strand, Janus and a restricted subset of the Concurrent Prolog family onto Dactl, a compiler target language based on graph rewriting. We discuss the problems found in the process and the adopted solutions. The paper contributes to related research by: # examining the potential of graph reduction as a suitable model for implementing CLLs in terms of expressiveness and efficiency

this paper we use TGRS and we exploit the high degree of fine grain parallelism available in the model in expressing a variety of concurrent object-oriented programming techniques. Being our framework language independent, it can serve as a basis for designing new concurrent Concurrent OOP using TGR techniques: George A Papadopoulos 2 object-oriented languages, implementing existing ones or act as a point of reference in comparing different approaches proposed by various languages to modelling certain OOP techniques such as delegation, inheritance, etc. but also to solving any associated problems encountered