[GSAS-II] Problem with sequential refinement of large data set

[Ivo Alxneit]

Dear all

I am having a problem with sequential refinements in GSASII. I have a
large data set where the changes to the few fitted parameters (scale
factor, one lattice parameter, three background parameters) are minor
and slow. If I fit a single pattern, the fit takes about one second
including saving the data. If I do a sequential refinement of less than
100 patterns (starting values are very close to final values in all
pattern) time to fit one pattern remains about the same. If I work with
1200 pattern the time increases to about three seconds. Finally, if I
use the whole series of 8500 patten the time to fit a single pattern
increases to about 45 seconds!

From my understanding the time to fit a single pattern in a sequential
refinement should be approximately constant as the fits are independent
of each other. I might expect a small increase of the time because the
data structure (project) becomes larger and so does the file that is
saved after each fit (8500 pattern: 1GB). The reality, however, shows a
more than linear increase of the time-per-pattern. How can this happen?
Where is more than 98% of the time spent?

In the same context. Shouldn't parallel execution of a sequential
refinement be "trivial" to be implemented: Each CPU grabs the next
pattern waiting to be refined and works on it. "Copy previous results"
would turn into "Get results from last refined pattern". These are
starting values and it should not make much of a difference if the are
from pattern n-1 or n-x (x being typically not too large).

Any insight is appreciated.
-- 
Dr. Ivo Alxneit
Catalysis for Energy Group
Bioenergy and Catalysis Laboratory        phone: +41 56 310 4092
Paul Scherrer Institute                     fax: +41 56 310 2688
CH-5232 Villigen                      gnupg key: 0x515E30C7
Switzerland
https://www.psi.ch/ceg/

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