The simulation speed and efficiency depends on the hardware and software that you use. Things that you should keep in mind are,
- Every computer is unique in its ability. So only someone with access to the exact same hardware (processor, gpu etc.) can test this out and tell you.
- As far as I know, there is no established method of calculating the computational time required for a calculation. But you can test this for yourself and get a scaling graph of how the number of atoms and cpu cores change the computational efficiency (This is valid only for a similar use case and so do not expect someone else's work to give a proper prediction).
That said, there actually are some things that you can try. First reduce the amount of dynamics that you simulate from
10ns to say a
several hundred pico seconds thereby reducing the computational time required. This way, you can achieve a very small calculation, at the end of which, you would see the computational speed prediction from the MD software (usually in the form of
ns/day). Once you know this, you can get an idea of how long the calculation might take for a
10ns dynamics length. However, do keep note that this estimation could have a small error and so it would be best to have some extra time allocated.
When doing this, remember that if the calculation writes files to the hard drive frequently, the time taken to write those files would slow the simulation down. This would be slightly difficult to account for in the initial short run. Also keep in mind that different ensembles have different computational speeds. For example, in my workstation, the NVE ensemble can be calculated around 50% faster than the NPT ensemble. However I do not know whether this is universal or not.
Also do note that as you proceed with your work, you would gain experience regarding the time taken for each calculation. With that experience, you would be able to get a pretty good guess of how long it takes (as long as the computer remains the same).
Since you seem to be just starting MD calculations, keep in mind that more cores is not always faster. Sometimes increasing the number of cores can reduce the computational efficiency by increasing communication time. So it would be best to try changing the number of cores allocated to see the configuration that gives the best performance.