3 ms·
Indeed, in terms of complexity theory I would guess, not in terms of milliseconds.
by wlievens 13y ago
Indeed, in terms of complexity theory I would guess, not in terms of milliseconds.
- jd007 13y agoRead http://en.wikipedia.org/wiki/Big_O_notation http://en.wikipedia.org/wiki/Big_O_notation Basically it's talking about time complexity, or how fast does the time it takes to compute the solution grow as the input grows in size.
- ginko 13y agoAn Algorithm with a lower time complexity will always take a shorter amount of time once the problem size grows large enough. You could run one algorithm on a modern cpu, utilizing Simd and tune for cache coherency and the other in QBASIC on an old 386 and the O(n log n) algorithm would still terminate earlier than the O(n^2) one past a certain n.