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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