In computer science, and more specifically in computability theory and computational complexity theory, a model of computation is a model that describes how an output of a mathematical function is computed given an input. A model of computation describes how units of computations, memories, and communications are organized. The computational complexity of an algorithm can be measured given a model of computation. Using a model allows studying the performance of algorithms independently of the variations that are specific to particular implementations and specific technology.
Categories Models of computation can be classified into three categories: sequential models, functional models, and concurrent models.
Sequential models
Some of these models have both deterministic and nondeterministic variants. Nondeterministic models are used in the study of computational complexity of algorithms. Models differ in their expressive power; for example, each function that can be computed by a finite-state machine can also be computed by a Turing machine, but not vice versa.
Uses In the field of runtime analysis of algorithms, it is common to specify a computational model in terms of primitive operations allowed which have unit cost, or simply unit-cost operations. A commonly used example is the random-access machine, which has unit cost for read and write access to all of its memory cells. In this respect, it differs from the above-mentioned Turing machine model.
See also
References
Further reading Fernández, Maribel (2009). Models of Computation: An Introduction to Computability Theory. Undergraduate Topics in Computer Science. Springer. ISBN 978-1-84882-433-1. Savage, John E. (1998). Models Of Computation: Exploring the Power of Computing. Addison-Wesley. ISBN 978-0201895391.
