In computational complexity theory, a speedup theorem is a theorem that for any algorithm (of a certain class) demonstrates the existence of a more efficient algorithm solving the same problem.1
Examples:
- Linear speedup theorem, that the space and time requirements of a Turing machine solving a decision problem can be reduced by a multiplicative constant factor.
- Blum's speedup theorem, which provides speedup by any computable function (not just linear, as in the previous theorem).
See also
See also
- Amdahl's law, the theoretical speedup in latency of the execution of a task at a fixed workload that can be expected of a system whose resources are improved.
References
References
- Blum, Manuel (1967-04-01). "A Machine-Independent Theory of the Complexity of Recursive Functions". J. ACM. 14 (2): 322–336. doi:10.1145/321386.321395. ISSN 0004-5411.