I wonder which one would be faster, of those opretion sets on computers, in float or double numbers:

1- four goniometric functions

vs

2- one square root and 1 inverse cosinus function

(I am assuming you mean trigonometric functions instead of goniometric functions)

Anyway, the correct answer is: Profile your code and test it yourself. My guess would be that the square root and one trigonometric function might be slightly faster, but I don't know which CPU you are using, so YMMV.

<insert obligatory rant about premature optimization here, blablabla>

My guess would be that the square root and one trigonometric function might be slightly faster, but I don't know which CPU you are using, so YMMV.

<insert obligatory rant about premature optimization here, blablabla>

Thanks for the guess tho, it is a cpu standard op, who knows of what advanced math lib, wheather intel or amd native ops, I believe they should not differ on this?

I think otherwise, inverse number is so expensive, while trigonometric functions can be aproximated by tylor polynomes in few degrees so well. I am going to profile, but I hope for more guesses :)

Thanks.

My guess would be that the square root and one trigonometric function might be slightly faster, but I don't know which CPU you are using, so YMMV.

<insert obligatory rant about premature optimization here, blablabla>

Thanks for the guess tho, it is a cpu standard op, who knows of what advanced math lib, wheather intel or amd native ops, I believe they should not differ on this?

I think otherwise, inverse number is so expensive, while trigonometric functions can be aproximated by tylor polynomes in few degrees so well. I am going to profile, but I hope for more guesses :)
Thanks.

What are you guys doing where trigonometric functions are used so heavily as to make a difference in performance?

What are you guys doing where trigonometric functions are used so heavily as to make a difference in performance ?

This is awfully dismissive, but go on then, I'll bite....

Actually, using lots of slerps in animation could be a valid reason. Although I would probably try to find some quick approximation in that case. A quick web search led me to this.

Don't worry, I've read all the literature. This was an example off the top of my head that would explain a scenario, but without getting into details that would break an NDA. Converting between Matrices/Quats/Eulers/Tan-quarter-angles spring to mind for trig funcs. Pow/log/exp and other such fun, are some of the bigger problems tbh.

You know, sqrt, abs and cbrt are usually per-formant enough to not worry. The rest of <cmath> is usually overkill in terms of accuracy for most people, there are faster alternatives that will do the job 95% of the time (and are often 10x to 50x faster). You might be of the opinion that those improvements aren't worth the cost/benefit analysis of implementing, which is fair enough. But if you have an opportunity to replace 2 of the expensive cmath calls with 1 (via some obscure maths identity), then you should always take it. My 2 cents. (Even if the only result is that you end up with 5 seconds extra battery life when your game is running on mobile - those 5s add up!)

Oh, and if anyone copies & pastes the Quake 3 reciprocal sqrt into their source code, go outside and shout: "I am a terrible human being!", repeatedly, for the rest of time.

I can get rid of divisions and square roots in so many cases by a little overload of trigonometry functions (that is why I seek big power in trigonometry). Even a deeper reforming of abstract logical problems to accomodate them. seems as an intense should-do.

Once reciprocaling or squarerooting, usualy something gets to suck even when it is done-, look at linear interpolating direction vectors to normalize them tardly afterwards , look at spherical coordinates on the other hand, combined with, that position vectors linearily interpolate good.

On cpu side, one can even make a 32bit integer number compact scalar field, and use it for high degree polynomes, now 10 scalared multiplications of integer numbers will give you a trigonometry value of extreme exactness for you to interpert in Real numbers? Imagine how much problems you can now screw up with such a trigonometric power waste.

Division and squareroot functions are impossible to aproximate by polynomes.

Frankly, I do not think that gpu's have any proccessing unit ops for trigonometry, since for long they were only using floating types for all instructions. While trigonometry is most needed in graphics (or possibly everywhere in my opinion).