Analysis of the programmed decrease in credit/hour in NanoHive@home:
Date ________ number of WUs ______ credit/hour _______ credit/hour ___ credit/hour _____ decrease __
_______________ in stats ___________ average ________ std-dev ______ min - max _____ in credit/hour
February 06 _______ 19 _______________ 48 _____________ 15 ________ 31 - 71 _______ starting point
February 07 _______ 18 _______________ 46 _____________ 23 ________ 21 - 92 __________ -5%
February 08 _______ 17 _______________ 38 _____________ 10 ________ 23 - 52 _________ -20%
February 09 _______ 17 _______________ 34 ______________ 7 ________ 21 - 40 _________ -30%
February 10 _______ 18 _______________ 23 ______________ 9 ________ 13 - 34 _________ -52%
February 11 _______ 12 _______________ 19 ______________ 6 ________ 13 - 27 _________ -60%
February 12 _______ 14 _______________ 22 ______________ 4 ________ 16 - 27 _________ -56%
February 13 _______ 14 _______________ 22 ______________ 5 _________ 9 - 27 _________ -56%
I have the strong impression that the programmed decrease is now getting quite slow. However, the numbers may be skewed by the fact that the WUs have been significantly longer for the last two days: five days ago the average length of the WUs was 25 000 seconds, today the averge length was 55 000 seconds - that is some 15 hours of crunching. Why this means higher credits/hour I do not know, but I have observed a similar trend in othe projects (such as QMC@Home, Simap).