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.
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.
Read more about this topic: Abstract Machine
Famous quotes containing the word information:
“Many more children observe attitudes, values and ways different from or in conflict with those of their families, social networks, and institutions. Yet today’s young people are no more mature or capable of handling the increased conflicting and often stimulating information they receive than were young people of the past, who received the information and had more adult control of and advice about the information they did receive.”
—James P. Comer (20th century)
“In the information age, you don’t teach philosophy as they did after feudalism. You perform it. If Aristotle were alive today he’d have a talk show.”
—Timothy Leary (b. 1920)
“So while it is true that children are exposed to more information and a greater variety of experiences than were children of the past, it does not follow that they automatically become more sophisticated. We always know much more than we understand, and with the torrent of information to which young people are exposed, the gap between knowing and understanding, between experience and learning, has become even greater than it was in the past.”
—David Elkind (20th century)