Actors A Model Of Concurrent Computation In Distributed Systems
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Actors: A Model of Concurrent Computation in Distributed Systems
A foundational model of concurrency is developed in this thesis. It examines issues in the design of parallel systems and show why the actor model is suitable for exploiting large-scale parallelism. Concurrency in actors is constrained only by the availability of hardware resources and by the logical dependence inherent in the computation. Unlike dataflow and functional programming, however, actors are dynamically reconfigurable and can model shared resources with changing local state. Concurrency is spawned in actors using asynchronous message-passing, pipelining, and the dynamic creation of actors. The author defines an abstract actor machine and provide a minimal programming language for it. A more expressive language, which includes higher level constructs such as delayed and eager evaluation, can be defined in terms of the primitives. Examples are given to illustrate the ease with which concurrent data and control structures can be programmed. This thesis deals with some central issues in distributed computing. Specifically, problems of divergence and deadlock are addressed. Additional keywords: Object oriented programming; Semantics.
Actors
The transition from sequential to parallel computation is an area of critical concern in today's computer technology, particularly in architecture, programming languages, systems, and artificial intelligence. This book addresses central issues in concurrency, and by producing both a syntactic definition and a denotational model of Hewitt's actor paradigm—a model of computation specifically aimed at constructing and analyzing distributed large-scale parallel systems—it substantially advances the understanding of parallel computation. Contents Introduction • General Design Decisions • Computation in ACTOR Systems • A More Expressive Language • A Model for ACTOR Systems • Concurrency Issues • Abstraction and Compositionality • Conclusions