Frequency Calculations Are Slow or Time Consuming about psi4

[susilehtola]

Why dertype='gradient'? If I am not mistaken, Psi4 does have analytic Hessians for Hartree-Fock.

The cost of quantum calculations increases non-linearly with the size of the system. It may well be that you are hitting the asymptotic scaling wall.

[loriab]

Be aware that analytic Hessians are available for Hartree–Fock (and a few DFT fctls that no one uses) only. So if wB97X-D is the target, it probably is best to prototype with freq(..., dertype='gradient') for consistency (as you were already doing). For all those displacements, QCFractal is the proposed way to run through them in parallel. You can get an idea how it works with a "snowflake" calc that just uses all the threads on a single node (and doesn't require database storage setup). conda-wise you'd need to conda install qcfractal postgresql -c conda-forge. An example is https://github.com/psi4/psi4/blob/master/tests/ddd-deriv/input.dat#L40-L47 . Snowflake is a lightweight single-node route. The full QCFractal approach is backed by a database (yours; not MolSSI's) and handles distributing gradient jobs through your cluster's queue. It takes a little more setup.

[Sulstice]

Thanks @loriab I went back through the chart in the documentation as well. This is useful and I think QC fractal is a way to go when we want to scale soon. We have own graph database structure under the hood that is different from relational databases so it would be good to rope into that.

The computation time is a lot faster and I obtain my thermodynamic analysis.

[Sulstice]

That was me playing around, trying to figure out when to use the different dertypes. The level of theory I will be using is w97X-D DFT perhaps in the future but with Hartree-Fock I wanted to test the code that I obtain something back.

I've always used the default before when calculating single point energy scans so when to apply to which different level of theory is a little lost on me.

dertype='energy'
dertype'gradient'

How would I get around this issue? In my mind

Option 1

Give it more juice (like CPU). If i have nodes on a cluster how do I distribute the job between the nodes perhaps.

Option 2

Play around with option parameters and maybe obtain orbitals from previous geometry? Is that faster?

https://psicode.org/psi4manual/master/autodir_options_c/scf__guess.html

Should I be changing into the guess parameter?

Update 1

I was playing around a bit more:

Module time:
	user time   =     221.38 seconds =       3.69 minutes
	system time =       8.88 seconds =       0.15 minutes
	total time  =         38 seconds =       0.63 minutes

The time decreased when I set the configurations to 'g_convergence': 'gau_loose' I think from gau_tight? dertype is still gradient.