You're probably right in that there is extensive writing to disk at this point.
I've run the apps on two different windows machines, one laptop with a whole load of memory and one old desktop with relatively little and they both seem to slow down at the same point which seems odd. I guess this has more to do with Windows' implementation of java than the configuration of the PC. Both are running XP.
My main problem seems to be with the ant example, which I've simply doubled the generations* & population size. As some experiments are run with far greater population sizes I was surprised that this was an issue even if there was serious bloat.
A test on a Linux/UNIX machine is required!
* This seems odd but I'm doing some research in this area
From: ECJ Evolutionary Computation Toolkit on behalf of Sean Luke
Sent: Sun 29/01/2006 19:14
To: [log in to unmask]
Subject: Re: Speed/Space
On Jan 29, 2006, at 10:07 AM, Dignum, Stephen A N wrote:
> I'm working through some of the GP examples in the apps directory.
> All work fine until I start to up the population size (doubling to
> 2048). I then get an out-of-memory error.
Actually, we use 2048 all the time and don't have much trouble, so
that's interesting to hear. Which examples are creating difficulty
> To get around this I increase the standard java memory parameters
> (Xmx, Xms, XX: etc), This works but if I then increase the number
> of generations past about 65 I get a sudden reduction in
> performance which isn't due to increase in program size i.e. number
> of nodes stays about the same. There may be a large increase in
> program depth but from my understanding of how ECJ works (by
> looking through the code!) it is the number of nodes that effects
> performance not depth.
ECJ's memory usage is fairly constant. In addition to a few small
constant elements, just after breeding time (the worst memory usage
case) ECJ has the current population _and_ the previous population
which was generated from it.
In the GP examples, individuals in the population have a constant
overhead each: the big loss comes from GPNodes, which take up (last
time I checked) about 32 bytes apiece. Compared to other methods,
it's a memory hog. I got into significant discussion of this, I
think, in the last tutorial.
So as the individuals grow in size due to bloat, it's perfectly
plausible for ECJ to be growing beyond your standard heap size. But
a sudden reduction in performance shouldn't ever happen if it's not
commensurate with a sudden increase in GP nodes. There is one
possibility though: you could be out of your sweet spot and are now
swapping badly. Could this be problems specific to Windows? We
typically run on Linux and OS X.
You can see the current memory usage and swap information by running
java -verbose:gc ...