Friday, March 11, 2016

Growth Rate - The Importance of Asymptotics

It really is true that if algorithm A is o(algorithm B) then for large problems A will take much less time than B.

Definition: If (the number of operations in) algorithm A is o(algorithm B), we call A asymptotically faster than B.

Example:: The following sequence of functions are ordered by growth rate, i.e., each function is little-oh of the subsequent function.
log(log(n)), log(n), (log(n))2, n1/3, n1/2, n, nlog(n), n2/(log(n)), n2, n3, 2n, 4n, n!

One way to compare 2 functions, is using L'Hospital rule. Here is good explanation:
Growth Rates of Functions and L'Hospital's Rule

Here is the snapshot of how the growth looks in increasing order
1 loglogn logn n nlogn n2 2n n! nn

Reference
https://cs.nyu.edu/courses/fall02/V22.0310-002/class-notes.html

http://www.cs.odu.edu/~cs381/cs381content/function/growth.html


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