Hi,
In addition to Carlos's excellent suggestions (use a larger
sieve/restrict clustering to a smaller subset of atoms) I have a few
more comments and suggestions
On Sat, May 22, 2021 at 9:43 AM Sruthi Sudhakar
<sruthisudhakarraji.gmail.com> wrote:
>
> trajin gamd2.nc
> loadcrd gamd2.nc 1 last 5 clus_crd
This is redundant. You're loading the trajectory for processing with
'trajin', but then reading that trajectory into a coordinates (COORDS)
data set with 'loadcrd' named "clus_crd" that you are then not using
in the subsequent 'cluster' command. So in effect you are using twice
the memory you need; the coordinates are stored in 'clust_crd' and
then again in the default coordinates set for "cluster". So either
remove the 'loadcrd' so that 'cluster' uses the default COORDS set, or
remove 'trajin' and add 'crdset clus_crd' to your 'cluster' command.
> Estimated memory usage (250000 frames): 83.211 GB
This indicates that you will need at least 83 GB to store the
coordinates in memory, and then more memory to store the pairwise
distance matrix, which maybe your analysis node does not have. So my
suggestion here would be to use the 'loadtraj' command to load the
coordinates as a 'TRAJ' (i.e. on-disk) data set, e.g.
parm noions.prmtop
loadtraj gamd2.nc name clus_crd
cluster crdset clus_crd sieve 10 ...
With 250k frames this means the single-precision pairwise matrix will
take about 1.2 GB of memory (if I did that math right); cpptraj should
print an estimate before clustering begins. So if you don't have that
much memory available you'll want to increase the sieve a bit.
With all that said, I really highly recommend you try the clustering
on a much smaller subset of your trajectory first (maybe 1000 frames
or so) just to make sure you have all your settings correct before you
jump right into clustering 250k frames.
Hope this helps,
-Dan
> ----- gamd2.nc (1-250000, 1) -----
> 0% 10% Killed
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Received on Sat May 22 2021 - 10:30:02 PDT
