Precomputation

Precomputation is the use in an algorithm of a (typically relatively expensive) initial computation, the results of which are then used to speed up later parts of that algorithm. The precomputation step may sometimes be expensive, and may often generate large data structures as a result, but can be used to greatly reduce the effort required in the later stage.

Precomputing a set of intermediate results at the beginning of an algorithm's execution can often increase algorithmic efficiency substantially. This becomes advantageous when one or more inputs is constrained to a small enough range that the results can be stored in a reasonably sized block of memory. Because memory access is essentially constant in time complexity (except for caching delays), any algorithm with a component which has worse than constant efficiency over a small input range can be improved by precomputing values. In some cases efficient approximation algorithms can be obtained by computing a discrete subset of values and interpolating for intermediate input values, since interpolation is also a linear operation.

Part of a 20th century table of common logarithms in the reference book Abramowitz and Stegun.

Before the advent of computers, printed lookup tables of values were used by people to speed up hand calculations of complex functions, such as in trigonometric tables, logarithm tables, and tables of statistical density functions^[1] School children are often taught to memorize "times tables" to avoid calculations of the most commonly used numbers (up to 9 x 9 or 12 x 12). Even as early as 493 A.D., Victorius of Aquitaine wrote a 98-column multiplication table which gave (in Roman numerals) the product of every number from 2 to 50 times and the rows were "a list of numbers starting with one thousand, descending by hundreds to one hundred, then descending by tens to ten, then by ones to one, and then the fractions down to 1/144" ^[2]

Even modern computer implementations of digital trigonometric algorithms often use precomputed lookup tables to either provide coefficients for interpolation algorithms or to initialise successive approximation algorithms.

Many attacks on cryptosystems involve precomputation.

Examples of large-scale precomputation as part of modern efficient algorithms include:

Rainbow tables
Perfect hashes
Precalculated BSP trees for visibility calculations in in 3D graphics
Radiosity precomputation for illumination in 3D graphics

Compilers use precomputation extensively as a means of increasing the run-time speed of the resulting code: this precomputation can be regarded as in effect a form of partial evaluation of the program code itself. Examples of this sort of precomputation include dataflow analysis and strength reduction steps.

References

^ Campbell-Kelly, Martin; Croarken, Mary; Robson, Eleanor, eds. (October 2, 2003) [2003]. The History of Mathematical Tables From Sumer to Spreadsheets (1st ed.). New York, USA: Oxford University Press. ISBN 978-0-19-850841-0. {{cite book}}: |access-date= requires |url= (help)
^ Maher, David. W. J. and John F. Makowski. "Literary Evidence for Roman Arithmetic With Fractions", 'Classical Philology' (2001) Vol. 96 No. 4 (2001) pp. 376-399. (See page p.383.)

References

See also