[R] runtime on ising model

[Mike Marchywka]

----------------------------------------
> Date: Tue, 26 Oct 2010 12:53:14 -0400
> From: mike409 at gmail.com
> To: jim at bitwrit.com.au
> CC: r-help at r-project.org
> Subject: Re: [R] runtime on ising model
>
> I have an update on where the issue is coming from.
>
> I commented out the code for "pos[k+1] <- M[i,j]" and the if statement for
> time = 10^4, 10^5, 10^6, 10^7 and the storage and everything ran fast(er).
> Next I added back in the "pos" statements and still runtimes were good
> (around 20 minutes).
>
> So I'm left with something is causing problems in:

I haven't looked at this since some passing interest in magnetics
decades ago, something about 8-tracks and cassettes, but you have
to be careful with conclusions like " I removed foo and problem
went away therefore problem was foo." Performance issues are often
caused by memory, not CPU limitations. Removing anything with a big
memory footprint could speed things up. IO can be a real bottleneck.
If you are talking about things on minute timescales, look at task
manager and see if you are even CPU limited. Look for page faults
or IO etc. If you really need performance and have a task which
is relatively simple, don't ignore c++ as a way to generate data
points and then import these into R for analysis. 

In short, just because you are focusing on math it doesn't mean
the computer is limited by that.


>
> ## Store state at time 10^4, 10^5, 10^6, 10^7
> if( k %in% c(10^4,10^5,10^6,10^7) ){
> q <- q+1
> Out[[q]] <- M
> }
>
> Would there be any reason R is executing the statements inside the "if"
> before getting to the logical check?
> Maybe R is written to hope for the best outcome (TRUE) and will just throw
> out its work if the logic comes up FALSE?
> I guess I can always break the for loop up into four parts and store the
> state at the end of each, but thats an unsatisfying solution to me.
>
>
> Jim, I like the suggestion of just pulling one big sample, but since I can
> get the runtimes under 30 minutes just by removing the storage piece I doubt
> I would see any noticeable changes by pulling large sample vectors.
>
> Thanks,
> Michael
>
> On Tue, Oct 26, 2010 at 6:22 AM, Jim Lemon  wrote:
>
> > On 10/26/2010 04:50 PM, Michael D wrote:
> >
> >> So I'm in a stochastic simulations class and I having issues with the
> >> amount
> >> of time it takes to run the Ising model.
> >>
> >> I usually don't like to attach the code I'm running, since it will
> >> probably
> >> make me look like a fool, but I figure its the best way I can find any
> >> bits
> >> I can speed up run time.
> >>
> >> As for the goals of the exercise:
> >> I need the state of the system at time=1, 10k, 100k, 1mill, and 10mill
> >> and the percentage of vertices with positive spin at all t
> >>
> >> Just to be clear, i'm not expecting anyone to tell me how to program this
> >> model, cause I know what I have works for this exercise, but it takes far
> >> too long to run and I'd like to speed it up by replacing slow operations
> >> wherever possible.
> >>
> >> Hi Michael,
> > One bottleneck is probably the sampling. If it doesn't grab too much
> > memory, setting up a vector of the samples (maybe a million at a time if 10
> > million is too big - might be able to rewrite your sample vector when you
> > store the state) and using k (and an offset if you don't have one big
> > vector) to index it will give you some speed.
> >
> > Jim
> >
> >
>
> [[alternative HTML version deleted]]
>
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