Distributed implementations of programming languages with implicit parallelism hold out the prospect that the parallel programs are immediately scalable. This paper presents some of the results of our part of Esprit 415, in which we considered the implementation of lazy functional programming languages on distributed architectures. A compiler and abstract machine were designed to achieve this goal. The abstract parallel machine was formally specified, using Miranda 1 . Each instruction of the abstract machine was then implemented as a macro in the Transputer Assembler. Although macro expansion of the code results in non-optimal code generation, use of the Miranda specification makes it possible to validate the compiler before the Transputer code is generated. The hardware currently available consists of five T800--25's, each board having 16M bytes of memory. Benchmark timings using this hardware are given. In spite of the straight forward code-generation, the resulting system compar...

We present a new parallel implementation of lazy ML. Our scheme is a direct extension of the G-machine-based implementation of lazy ML. Parallelism is introduced by fork annotations inserted by the programmer. We discuss the interference of such user annotations with strictness annotations generated by our compiler. The system has been implemented on a Sequent Balance computer. We also address the main practical issues involved, including stack and heap management. 1 Introduction The object of this work is to demonstrate that a lazy runtime system such as the G-machine may be implemented efficiently on a parallel shared-memory computer. It is natural to consider parallelism in a language without side effects. Its semantics guarantee that it is possible to evaluate subexpressions in any order (Church-Rosser property). From a more operational point of view it can be observed that a lazy runtime system already provides facilities for delaying evaluations and that it should be relativel...

A new technique for the management of runtime structures in distributed implementations is presented. Instead of storing the runtime stacks of parallel processes as linked lists of function blocks in a heap structure, the local stacks of several parallel processes, which are executed on the same processor element, are stored in an interleaved manner on a single physical stack, called the meshed stack. The technique originated from the stack organisation in the well known Warren Abstract Machine (WAM) for logic languages, where the runtime information of several alternative computation branches is stored on a single stack.

The evaluation transformer model of reduction generalises lazy evaluation in two ways: it can start the evaluation of expressions before their first use, and it can evaluate expressions further than weak head normal form. Moreover, the amount of evaluation required of an argument to a function may depend on the amount of evaluation required of the function application. It is a suitable candidate model for implementing lazy functional languages on parallel machines. In this paper we explore the implementation of lazy functional languages on parallel machines, both shared and distributed memory architectures, using the evaluation transformer model of reduction. We will see that the same code can be produced for both styles of architecture, and the definition of the instruction set is virtually the same for each style. The essential difference is that a distributed memory architecture has one extra node type for non-local pointers, and instructions which involve the value of such nodes need their definitions extended to cover this new type of node. To make our presentation accessible, we base our description on a variant of the well-knon G-machine, a machine for executing lazy functional programs.

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...

A clustered architecture has been designed to exploit divide and conquer parallelism in functional programs. The programming methodology developed for the machine is based on explicit annotations and program transformations. It has been successfully applied to a number of algorithms resulting in a benchmark of small and medium size parallel functional programs. Sophisticated compilation techniques are used such as strictness analysis on non-flat domains and RISC and VLIW code generation. Parallel jobs are distributed by an efficient hierarchical scheduler. A special processor for graph reduction has been designed as a basic building block for the machine. A prototype of a single cluster machine has been constructed with stock hardware. This paper describes the experience with the project and its current state. 1 Introduction Functional programming is founded on the lambda calculus, which is a mathematical theory that provides a sound basis for work on reduction machines [5]. This is p...