We survey parallel programming models and languages using 6 criteria [:] should be easy to program, have a software development methodology, be architecture-independent, be easy to understand, guranatee performance, and provide info about the cost of programs. ... We consider programming models in 6 categories, depending on the level of abstraction they provide.

Programming parallel computers remains a difficult task. An ideal programming environment should enable the user to concentrate on the problem solving activity at a convenient level of abstraction, while managing the intricate low-level details without sacrificing performance. This thesis investigates a model of parallel programming based on the BirdMeertens Formalism (BMF). This is a set of higher-order functions, many of which are implicitly parallel. Programs are expressed in terms of functions borrowed from BMF. A parallel implementation is defined for each of these functions for a particular topology, and the associated execution costs are derived. The topologies which have been considered include the hypercube, 2-D torus, tree and the linear array. An analyser estimates the costs associated with different implementations of a given program and selects a cost-effective one for a given topology. All the analysis is performed at compile-time which has the advantage of reducing run-...

The research presented in this thesis is about the design and implementation of Naira, a parallel, parallelising compiler for a rich, purely functional programming language. The source language of the compiler is a subset of Haskell 1.2. The front end of Naira is written entirely in the Haskell subset being compiled. Naira has been successfully parallelised and it is the largest successfully parallelised Haskell program having achieved good absolute speedups on a network of SUN workstations. Having the same basic structure as other production compilers of functional languages, Naira's parallelisation technology should carry forward to other functional language compilers. The back end of Naira is written in C and generates parallel code in the C language which is envisioned to be run on distributed-memory machines. The code generator is based on a novel compilation scheme specified using a restricted form of Milner's ß-calculus which achieves asynchronous communication. We present the f...

Abstract. The spreadsheet paradigm offers a fast interactive loop, where the effects of updates to definitions and data are immediately visible. This makes the paradigm attractive for program development, where redefinitions can be immediately tested and the results displayed. We have designed a simple, compilerindependent spreadsheet interface to Haskell, where cells host Haskell definitions. Spreadsheets are also used for high-level array calculations. In order to meet that demand we have designed and implemented an extended array library for Haskell, which provides a number of typical array-language facilities. Together, the interface and the array library provide an interactive environment that can be used both for development of general Haskell code and for array-oriented spreadsheet calculations.

Indexed data structures are prevalent in many programming applications. Collection-oriented languages provide means to operate directly on these structures, rather than having to loop or recurse through them. This style of programming will often yield clear and succinct programs. However, these programming languages will often provide only a limited choice of indexed data types and primitives, and the exact semantics of these primitives will sometimes vary with the data type and language. In this paper we develop a unifying semantical model for indexed data structures. The purpose is to support the construction of abstract data types and language features for such structures from first principles, such that they are largely generic over many kinds of data structures. The use of these abstract data types can make programs and their semantics less dependent of the actual data structure. This makes programs more portable across different architectures and facilitates the early design phase. The model is a generalisation of arrays, which we call data fields: these are functions with explicit information about their domains. This information can be conventional array bounds but it could also define other shapes, for instance sparse. Data fields can be interpreted as partial functions, and we define a metalanguage for partial functions. In this language we define abstract versions of collection-oriented operations, and we show a number of identities for them. This theory is used to guide the design of data fields and their operations so they correspond closely to the more abstract notion of partial functions. We define phi-abstraction, a lambda-like syntax for defining data fields in a shape-independent manner, and prove a theorem which relates phi-abstraction and lambda-abstraction semantically. We also define a small data field language whose semantics is given by formal data fields, and give examples of data field programming for parallel algorithms with arrays and sparse structures, database quering and computing, and specification of symbolic drawings.

. Data fields provide a flexible and highly general model for indexed collections of data. Data Field Haskell is a Haskell dialect that provides an instance of data fields. It can be used for very generic collection-oriented programming, with a special emphasis on multidimensional structures. We give a brief description of the data field model and its underlying theory. We then describe Data Field Haskell, and an implementation. 1 Introduction Indexed data structures are important in many computing applications. The canonical indexed data structure is the array, but other indexed structures like hash tables and explicitly parallel entities are also common. In many applications the indexing capability provides an important part of the model: when solving partial differential equations, for instance, the index is often closely related to a physical coordinate, and explicitly parallel algorithms often use processor ID's as indices. Since the time of APL [5] it has been recognised ...

One of the most serious shortcomings of multidimensional languages is their inability to collaborate with conventional programming languages and systems. Multidimensional languages are used in order to define (potentially infinite) streams, grids, cubes, and so on, concepts which resemble in nature to the familiar imperative arrays. The main difference is that the former entities are lazy while the latter are generally eager. This paper proposes the embedding of multidimensional languages into conventional ones as a form of definitional lazy arrays. The paper describes the details of an implementation of the proposed idea as well as the expressibility and the performance of the resulting system. The main advantage of the new approach is that multidimensional languages can now benefit from the advanced features that have been developed for conventional languages. Moreover, multidimensionality adds to conventional languages the idea of lazy arrays, which in many cases o#er significant advantages compared to the classical imperative arrays.

. Data fields are partial functions provided with explicit domain information. They provide a very general, formal model for collections of data. Algorithms computing data collections can be described in this formalism at various levels of abstraction: in particular, explicit data distributions are easy to model. Parallel versions of algorithms can then be formally verified against algorithm specifications in the model. Functions computing data fields can be directly programmed in the language Data Field Haskell. In this paper we give a brief introduction to the data field model. We then describe Data Field Haskell and make a small case study of how an algorithm and a parallel version of it both can be specified in the language. We then verify the correctness of the parallel version in the data field model. 1 Introduction Many computing applications require indexed data structures. In many applications the indexing capability provides an important part of the model. On the ...

This paper presents the results of a study in which we examined about 50 parallel programming languages in order to detect typical approaches towards supporting massive parallelism. Based on a classification into nine classes, semantic properties affecting the development of parallel programs are compared. From a consideration of the general function of programming languages in software engineering, we derive basic requirements on parallel languages.