We develop a generic programming language for parallel algorithms, one that works for all data structures and control structures. We show that any parallel algorithm satisfying intuitively-appealing postulates can be ...
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We develop a generic programming language for parallel algorithms, one that works for all data structures and control structures. We show that any parallel algorithm satisfying intuitively-appealing postulates can be modelled by a collection of cells, each of which is an abstract state machine, augmented with the ability to spawn new cells. The cells all run the same algorithm and communicate via a shared global memory. Using a formal definition of what makes such an algorithm effective, we prove the validity of the parallel computation thesis, according to which all reasonable parallel models of computation have roughly equivalent running times.
Studies of issues related to computability and computational complexity involve the use of a model of computation. Central in such a model are computational processes. Processes of this kind can be described using an ...
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Studies of issues related to computability and computational complexity involve the use of a model of computation. Central in such a model are computational processes. Processes of this kind can be described using an imperative process algebra based on ACP (Algebra of Communicating Processes). In this paper, it is investigated whether the imperative process algebra concerned can play a role in the field of models of computation. It is demonstrated that the process algebra is suitable to describe in a mathematically precise way models of computation corresponding to existing models based on sequential, asynchronous parallel, and synchronous parallel random access machines as well as time and work complexity measures for those models.
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