Looking at my old data, I can see that writing out of data between each
global fit analysis before took around 30 min.
They now take 2-6 mins.
I almost can't believe that speed up!
Could we devise a devel-script, which we could use to simulate the change?
Best
Troels
2014-06-04 14:24 GMT+02:00 Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx>:
Hi Edward.
After the changes to the lib/dispersion/model.py files, I see massive
speed-up of the computations.
During 2 days, I performed over 600 global fittings for a 68 residue
protein, where all residues where clustered.I just did it with 1 cpu.
This is really really impressive.
I did though also alter how the grid search was performed, pre-setting
some of the values from known values referred to in a paper.
So I can't really say what has cut the time down.
But looking at the calculations running, the minimisation runs quite fast.
So, how does relax do the collecting of data for global fitting?
Does i collect all the R2eff values for the clustered spins, and sent it
to the target function
together with the array of parameters to vary?
Or does it calculate per spin, and share the common parameters?
My current bottle neck actually seems to be the saving of the state file,
between each iteration of global analysis.
Best
Troels
Re: How is the R2eff data collected and processed for clustered analysis?