Re: is double slower?

On 04/11/2024 08:53, fir wrote:

float takes less space and when you keep arrays of floats for sure float
is better (less spase and uses less memory bandwidth so i guess floats
can be as twice faster in some aspects)
 

Certainly if you have a lot of them, then the memory bandwidth and cache it rate can make floats faster than doubles.

but when you do calculations on local variables not floats do the double is slower?

I assume that for the calculations in question, the accuracy and range of float is enough - otherwise the answer is obviously use doubles.
This is going to depend on the cpu, the type of instructions, the source code in question, the compiler and the options.  So there is no single easy answer.
You can, as Bonita suggested, look up instruction timing information at agner.org for the cpu you are using (assuming it's an x86 device) to get some idea of any fundamental differences in timings.  Usually for modern "big" processors, basic operations such as addition and multiplication are single cycle or faster (i.e., multiple instructions can be done in parallel) for float and double.  But division, square root, and other more complex operations can take a lot longer with doubles.
Next, consider if you can be using vector or SIMD operations.  On some devices, you can do that with floats but not doubles - and even if you can use doubles, you can usually run floats at twice the rate.
In the source code, remember it is very easy to accidentally promote to double when writing in C.  If you want to stick to floats, make sure you don't use double-precision constants - a missing "f" suffix can change a whole expression into double calculations.  Remember that it takes time to convert between float and double.
Then look at your compiler flags - these can make a big difference to the speed of floating point code.  I'm giving gcc flags, because those are the ones I know - if you are using another compiler, look at the details of its flags.
Obviously you want optimisation enabled if speed is relevant - -O2 is a good start.  Make sure you are optimising for the cpu(s) you are using - "-march=native" is good for local programs, but you will want something more specific if the binary needs to run on a variety of machines.  The closer you are to the exact cpu model, the better the code scheduling and instruction choice can be.
Look closely at "-ffast-math" in the gcc manual.  If that is suitable for your code (and it often is), it can make a huge difference to floating point intensive code.  If it is unsuitable because you have infinities, or need deterministic control of things like associativity, it will make your results wrong.
"-Wdouble-promotion" can be helpful to spot accidental use of doubles in what you think is a float expression.  "-Wfloat-equal" is a good idea, especially if you are mixing floats and doubles.  "-Wfloat-conversion" will warn about implicit conversions from doubles to floats (or to integers).