The limits of computation are governed by a number of different factors. In particular, there are several physical and practical limits to the amount of computation or data storage that can be performed with a given amount of mass, volume, or energy.

Hardware limits or physical limits

Processing and memory density

Processing speed

Communication delays

Energy supply

kT ln 2 consumed per irreversible state change, where k is the Boltzmann constant and T is the operating temperature of the computer. Reversible computing is not subject to this lower bound. T cannot, even in theory, be made lower than 3 kelvins, the approximate temperature of the cosmic microwave background radiation, without spending more energy on cooling than is saved in computation. However, on a timescale of 109 – 1010 years, the cosmic microwave background radiation will be decreasing exponentially, which has been argued to eventually enable 1030 as much computations per unit of energy. Important parts of this argument have been disputed.

Building devices that approach physical limits

Several methods have been proposed for producing computing devices or data storage devices that approach physical and practical limits:

Abstract limits in computer science

In the field of theoretical computer science the computability and complexity of computational problems are often sought-after. Computability theory describes the degree to which problems are computable, whereas complexity theory describes the asymptotic degree of resource consumption. Computational problems are therefore confined into complexity classes. The arithmetical hierarchy and polynomial hierarchy classify the degree to which problems are respectively computable and computable in polynomial time. For instance, the level of the arithmetical hierarchy classifies computable, partial functions. Moreover, this hierarchy is strict such that at any other class in the arithmetic hierarchy classifies strictly uncomputable functions.

Loose and tight limits

Many limits derived in terms of physical constants and abstract models of computation in computer science are loose. Very few known limits directly obstruct leading-edge technologies, but many engineering obstacles currently cannot be explained by closed-form limits.