Slow AIMD Calculations and Memory Issues

[Jawad Elhamdaoui]

Dear CP2K Community,

I am facing issues with my AIMD calculations. My system has 162 atoms and runs on an HPC setup with 500 CPUs. The Problem Is that each step takes ~15 minutes, and I also encounter out-of-memory errors.

I suspect the issues might be due to input settings or parallelization inefficiencies. Could you please advise how to optimize performance and memory usage for a system of this size?

I appreciate your help!

Best regards,

[Jawad Elhamdaoui]

Dear CP2K Community,

I am facing issues with my AIMD calculations. My system size is 162 atoms, and I run on an HPC setup of 500 CPUs. Each step takes ~15 minutes, and I also encounter out-of-memory errors.

I suspect the issues might be due to input settings or parallelization inefficiencies. Could you please advise how to optimize performance and memory usage for a system of this size?

I appreciate your help!

  Best regards,

Jawad

[Frederick Stein]

Dear Jawad,

Without any output file, it is hard to guess what the issue is. Could you maybe run a short MD (a few frames) and provide the output file? I am especially interested in the statistics part at the end of the output file (Timing report, "MEMORY| Estimated peak process memory [MiB]"). Please provide the full input file you used (not necessarily the geometry files) because you commented out the cell definition in your input file.

Best,

Frederick

[Jawad Elhamdaoui]

Dear Frederick,

Thank you for your prompt response.

Please find attached the output file. Regarding the input, I used the same file I uploaded earlier, but I commented out the cell part to restart the calculationa and add the restart part.

Please let me know if you need any further details.

Best regards

Jawad 

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[Jawad Elhamdaoui]

 Dear Frederick,

Thank you for your response.

I hope that the output file is uploaded correctly. It says that it exceeds the 8 Mb limit, so I removed some in the middle.

Please let me know if you need any further details.

Best regards

Jawad

[Frederick Stein]

There is no output file. You can remove all steps except from one. In doubt, compress it or share a link to the output file.

[Jawad Elhamdaoui]

Dear Frederick,

Thank you for your prompt response.

Please find attached the output file. Regarding the input, I used the same file I uploaded earlier, but I commented out the cell part to restart the calculation and add the restart part.

Please let me know if you need any further details.

Best regards

Jawad 

To view this discussion visit https://groups.google.com/d/msgid/cp2k/ade71ae0-4617-4824-adc9-4c782057c7f6n%40googlegroups.com.

[Frederick Stein]

Dear Jawad,

I checked your timings. The time per SCF iteration is acceptable to me. The issue is that your system converges quite slowly in the very first step. To improve convergence, you can

- reduce MAX_SCF in the inner convergence loop. This rebuilds the preconditioner more often and may help with convergence.

- try FULL_ALL for preconditioning

- try a different minimizer (DIIS or BROYDEN instead of CG)

- adjust ENERGY_GAP to a value lower than your actual gap. Too low value slow down convergence, too high values prevent convergence.

Did you check whether the numerical stress tensors are actually faster than analytical stress tensors?

Is there a reason why you work with CP2K 8.2?

Regarding you MPI error: This seems to be related to your MPI implementation, NOT to CP2K. What MPI distribution do you use (library name+version)?

Best,

Frederick

[Jawad Elhamdaoui]

Dear Frederick,

Thank you for your prompt response and helpful suggestions.

I haven’t yet checked whether the numerical stress tensors are faster than the analytical ones. I initially chose the numerical option thinking it might provide better accuracy, but I will test the analytical stress tensors as well to compare performance.

As for CP2K 8.2, there is no specific reason for using this version—it’s simply the version currently installed on our HPC.

Regarding the MPI error, I am using mpirun (Open MPI) 4.1.1.

Thank you again for your time and assistance. I will implement your suggestions and let you know the outcomes.

Best regards,
Jawad