Michael S (already5chosen.delete@this.yahoo.com) on January 24, 2017 9:05 am wrote:
> tarlinian (tarlinian.delete@this.gmail.com) on January 24, 2017 8:58 am wrote:
> > Niels Jørgen Kruse (nj_kruse.delete@this.me.com) on January 23, 2017 10:41 pm wrote:
> > > Aaron Spink (aaronspink.delete@this.notearthlink.net) on January 23, 2017 7:01 pm wrote:
> > > > Niels Jørgen Kruse (nj_kruse.delete@this.me.com) on January 22, 2017 12:16 pm wrote:
> > > > > In weather prediction, you do ensemble runs anyway.
> > > > >
> > > > >
> > > >
> > > > Because it is a statistical model, but now you have to do backup runs for each of your
> > > > ensemble runs because you don't know how out of whack they got from memory errors.
> > > > In any reasonable sized super, you are going to have daily/hourly memory errors.
> > >
> > > It would be more rational to increase the ensemble. It doesn't
> > > matter why any particular run deviates from the majority.
> >
> > That really doesn't make physical sense. The "noise" generated
> > by random bit flips likely comes from a completely
> > different distribution than the noise that the "noise" that results from initial condition perturbations.
>
> As long as you apply statistical filtering (median or similar) to the results, it does not matter.
> Only one condition is important: percentage of the runs that are affected by memory errors shell be low.

that largely depends on the size of the machine and the time to do a run and the altitude.