Hi,
You are likely running out of memory. This is why your problems during
clustering went away when you reduced the number of input frames by a
factor of 5. The solution is to do everything on disk. So instead of
loading all coordinates into memory, separate the principal component
analysis into three separate phases:
1) Create average coordinates.
2) Rms fit your trajectory to average coordinates, calculate the
covariance matrix, write out the fit trajectory, diagonalize the
matrix and write out the "modes" data (i.e. eigenvectors and
eigenvalues).
3) Read in the "modes" data, calculate principal component projections
from the fit trajectory, do the Kullback-Leibler divergence analysis.
This way, the most memory you need is to store the covariance matrix,
modes, and other data of that type. Hope this helps,
-Dan
PS - Note that there appears to be a small error in the input you
posted (in pca.in). The 'nmwiz' keyword should be part of the
diagmatrix command, not on a separate line.
On Mon, May 31, 2021 at 1:22 PM Sruthi Sudhakar
<sruthisudhakarraji.gmail.com> wrote:
>
> Dear all,
>
> I have been doing pca analysis on an accelerated MD trajectory of 500ns
> (250,000 frames). I have attached the input file I have used for the study.
> The job stops at the createcrd stage. Basically, the job gets killed at
> 30%. The same happened during the cluster analysis reading every frames.
> The clustering error was solved when I changed the input to read every 5th
> frame. Now since this is repeating in pca analysis, kindly help regarding
> the same.
>
>
> Regards,
> Sruthi Sudhakar
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Received on Tue Jun 01 2021 - 06:30:03 PDT
