The join-calculus is both a name passing calculus and a core language for concurrent and distributed programming. An essential part of its implementation is the compilation of join-patterns. Join-patterns define new channels and all the synchronizations they take part to at the same time. Relying on the experience based on our two implementations, we study the translation of join-patterns into deterministic finite-state automata as well as some related optimizations. 1 Introduction Join-pattern is the distinctive feature of the join-calculus, seen both as a process calculus and as a programming language. On the calculus side, join-calculus can roughly be seen as a functional calculus plus join-patterns, thus achieving the same expressive power as previous name-passing process calculi [11]. Joindefinitions are made of several clauses, each clause being a pair of a join-pattern and of a guarded process. A join-pattern expresses a synchronization between several names (or channels). When...

In ML style pattern matching, pattern size is not constrained and ambiguous patterns are allowed. This generality leads to a clear and concise programming style but is challenging in the context of lazy evaluation. A first challenge concerns language designers: in lazy ML, the evaluation order of expressions follows actual data dependencies. That is, only the computations that are needed to produce the final result are performed. Once given a proper (that is, non-ambiguous) semantics, pattern matching should be compiled in a similar spirit: any value matching a given pattern should be recognized by performing only the minimal number of elementary tests needed to do so. This challenge was first met by A. Laville. A second challenge concerns compiler designers. As it stands, Laville's compilation algorithm cannot be incorporated in an actual lazy ML compiler for efficiency and completeness reasons. As a matter of fact, Laville's original algorithm did not fully treat the case of intege...

We present improvements to the backtracking technique of pattern-matching compilation. Several optimizations are introduced, such as commutation of patterns, use of exhaustiveness information, and control ow optimization through the use of labeled static exceptions and context information. These optimizations have been integrated in the ObjectiveCaml compiler. They have shown good results in increasing the speed of pattern-matching intensive programs, without increasing nal code size.

Modern, statically typed, functional languages define functions by pattern matching. Although pattern matching is defined in terms of sequential checking of a value against one pattern after another, real implementations translate patterns into automata that can test a value against many patterns at once. Decision trees are popular automata.

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...

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