Type-Based Complexity Analysis for Fork Processes
Identifieur interne : 001458 ( Main/Exploration ); précédent : 001457; suivant : 001459Type-Based Complexity Analysis for Fork Processes
Auteurs : Emmanuel Hainry [France] ; Jean-Yves Marion [France] ; Romain Péchoux [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
English descriptors
- mix :
Abstract
Abstract: We introduce a type system for concurrent programs described as a parallel imperative language using while-loops and fork/wait instructions, in which processes do not share a global memory, in order to analyze computational complexity. The type system provides an analysis of the data-flow based both on a data ramification principle related to tiering discipline and on secure typed languages. The main result states that well-typed processes characterize exactly the set of functions computable in polynomial space under termination, confluence and lock-freedom assumptions. More precisely, each process computes in polynomial time so that the evaluation of a process may be performed in polynomial time on a parallel model of computation. Type inference of the presented analysis is decidable in linear time provided that basic operator semantics is known.
Url:
DOI: 10.1007/978-3-642-37075-5_20
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">Abstract: We introduce a type system for concurrent programs described as a parallel imperative language using while-loops and fork/wait instructions, in which processes do not share a global memory, in order to analyze computational complexity. The type system provides an analysis of the data-flow based both on a data ramification principle related to tiering discipline and on secure typed languages. The main result states that well-typed processes characterize exactly the set of functions computable in polynomial space under termination, confluence and lock-freedom assumptions. More precisely, each process computes in polynomial time so that the evaluation of a process may be performed in polynomial time on a parallel model of computation. Type inference of the presented analysis is decidable in linear time provided that basic operator semantics is known.</div>
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