Abstract machine

Not to be confused with Virtual machine.

An abstract machine, also called an abstract computer, is a theoretical model of a computer hardware or software system used in automata theory. Abstraction of computing processes is used in both the computer science and computer engineering disciplines and usually assumes a discrete time paradigm.

Information

In the theory of computation, abstract machines are often used in thought experiments regarding computability or to analyze the complexity of algorithms (see computational complexity theory). A typical abstract machine consists of a definition in terms of input, output, and the set of allowable operations used to turn the former into the latter. The best-known example is the Turing machine.

Abstract data types can be specified in terms of their operational semantics on an abstract machine. For example, a stack can be specified in terms of operations on an abstract machine with an array of memory.

More complex definitions create abstract machines with full instruction sets, registers and models of memory. One popular model more similar to real modern machines is the RAM model, which allows random access to indexed memory locations. As the performance difference between different levels of cache memory grows, cache-sensitive models such as the external-memory model and cache-oblivious model are growing in importance.

An abstract machine can also refer to a microprocessor design which has yet to be (or is not intended to be) implemented as hardware. An abstract machine implemented as a software simulation, or for which an interpreter exists, is called a virtual machine.

Through the use of abstract machines it is possible to compute the amount of resources (time, memory, etc.) necessary to perform a particular operation without having to construct an actual system to do it.

Other abstract machines

See also

References

This article is based on material taken from the Free On-line Dictionary of Computing prior to 1 November 2008 and incorporated under the "relicensing" terms of the GFDL, version 1.3 or later.

  1. ↑ D. B. Skillicorn (2005). Foundations of Parallel Programming. Cambridge University Press. p. 18. ISBN 978-0-521-01856-2.

Further reading

Jan van Leeuwen, ed. "Handbook of Theoretical Computer Science. Volume A: Algorithms and Complexity, The MIT PRESS/Elsevier, 1990. ISBN 0-444-88071-2 (volume A). QA 76.H279 1990.
This article is issued from Wikipedia - version of the 11/2/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.