20160204, 14:18  #1 
"Ron"
Jan 2016
Fitchburg, MA
61_{16} Posts 
roundoff = 0.224. Normal? Yes. [solved]
New to the project and have been trying to do as much reading as possible to learn more with out having to post every 2 seconds, but I was wondering if someone could weigh in on the following.
Code:
Iteration: 59080000 / 76088891 [77.64%], roundoff: 0.224, ms/iter: 7.160, ETA: 33:49:49 
20160204, 14:58  #2  
Banned
"Luigi"
Aug 2002
Team Italia
5^{2}·193 Posts 
Quote:
The roundoff happens because doubleprecision numbers are used in place of integers to either speed up or optimize the algorithm: as long as it is kept below a defined threshold, it's not obnoxious and does not indicate a hardware malfunction. Happy crunching! Last fiddled with by ET_ on 20160204 at 14:59 

20160204, 22:07  #3  
Serpentine Vermin Jar
Jul 2014
6361_{8} Posts 
Quote:
If those > 0.4 occur frequently it could be a case of the FFT size being too small for that exponent, but it could indicate hardware problems too. For 0.224 I wouldn't worry too much. 

20160205, 00:01  #4 
"Curtis"
Feb 2005
Riverside, CA
4,943 Posts 
To add a little bit to their quality answers:
If roundoff error were exactly 0.5, we wouldn't know if the number was meant to be rounded down or rounded up so the result of the floatingpoint calculation, when converted back to integer, would be wrong 50% of the time (since the algo would, in a sense, guess which way to round). If roundoff error exceeds 0.4, say, 0.4125, there's a chance it's really a roundoff error of 0.5875 from the adjacent integer. The difference between 0.4 and 0.6 is large enough that roundoff errors below 0.4 are ignored and considered accurate when rounded, but 0.4 to 0.5 causes the program to redo the calculation with a more accurate floatingpoint algorithm to decrease the error inherent to these calculations. Short version: a result of 34563456.5 is unclear from the FPU algo, because we don't know which way to round back to integerland. A result of 34563456.46 is clear, but slightly dangerous because the real value might be 34453457 but the FPU had roundoff error of 0.54; so, that calc is redone with a more accurate but slower method. Results like 34563456.22 are clear, and not in danger of being accidentally rounded wrong. 
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