As for pow. I did a quick test to see how slow Math. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. Pow vs multiply operator performance Ask Question. Asked 12 years, 5 months ago. Active 4 months ago. Viewed 56k times. Anyone knows if multiply operator is faster than using the Math.
Pow method? Pow n, 3. Improve this question. Deduplicator Joan Venge Joan Venge k gold badges silver badges bronze badges. The way to achieve performance is 1 set meaningful goals, 2 measure to see if you've met your goals, 3 find the slowest thing if you haven't, 4 optimize the slowest thing until your goal is met. If you have to ask us which is faster then you haven't done steps 2 or 3 , and so it is premature to do step 4. Add a comment.
Active Oldest Votes. I just reinstalled windows so visual studio is not installed and the code is ugly using System; using System. WriteLine "Math. Pow: ms: 4. NET version is 3. Improve this answer. Community Bot 1 1 1 silver badge. Your method seems very good. Is it even better than n n n? It requires two multiplications, just like n n n, but with some overhead, so it will be slightly worse MyPow works just only for positive numbers.
Abs exp ; — Miroslav Holec. I just ran this on my laptop but as a. NET Core 2. Pow: ms. So obviously MS has improved the performance a lot since this was posted. Basically, you should benchmark to see. Educated Guesswork unreliable : In case it's not optimized to the same thing by some compiler It takes two integer multiply instructions. In case Math. Improve this answer. Thanks for an answer! I actualy tested it in a loop with bilion of iterations to get a decent results..
Kayaman Kayaman Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. The Overflow Blog. Does ES6 make JavaScript frameworks obsolete? Podcast Do polyglots have an edge when it comes to mastering programming Featured on Meta. Now live: A fully responsive profile. It seems the algorithm used for approximation of the power does not depend on the exponent itself at least between 3 and 4.
One compiler option is very important to consider here: -ffast-math. This compiler option will make some math operations much faster, but will also violate a lot of IEEE compliance.
In most cases, it does not matter since this will mostly cover edge cases resulting in infinities and Not-A-Numbers. It also will reduce the accuracy of some operations.
If you really care about precise computation, you should not use -ffast-math, but in most case, I think it's fine. Any way, let's see if that changes anything:. For the third power, for std::pow x, 3 , it is now much faster than before. Let's see if there are differences between clang Moreover, there is no difference between the two libraries. Let's see if this makes a difference for third power:. I was expecting more of a difference between the two, but it seems they are using a similar implementations, if not the same.
As said earlier, all the tests were run in single precision float. Let's see now if it's any different with double precision double. This is very interesting! It seems that most of the overhead of this function for single precision was in fact in conversion to double since it seems that the algorithm itself is only implemented for double precision. Let's see about third power now:.
As seen before, with third power, the overhead is actually huge. Let's see what happens with -ffast-math:. With -ffast-math, there is absolutely no overhead anymore for std::pow x, n even for third power.
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