Scaling Clustered Evolution: 1 + 1 = 4

This is a follow up on: http://rogeralsing.com/2009/01/01/clustering-evolution-we-have-lift-off/

Yesterday I got the chance to test run the cluster version of EvoLisa on a 64 bit 4 core machine.
(Thanks to my collegue Ulf Axelsson for the help on this one)

The results from the cluster version are quite interesting.
One could expect that you would get a maximum of 200% performance by using two nodes instead of one.
However, this is not the case, **we are getting 400% performance by doing this. **

Doubling the CPU capacity and get 4 times as much work done.

How is this possible?

This really confused me for a while.
But the reason is quite obvious once you figure it out.

Let’s assume the following:

* We use one core.
* We are running 1000 generations with 50 polygons over 10 seconds.
* 1 out of 10 mutations are positive.

This gives us approx 100 positive mutations over 10 seconds.

If we add one more core we would get:

* We use two cores in parallel.
* We are running a total of 2000 generations, with 50 polygons per node over 10 seconds.
* 1 out of 10 mutations are positive.

This would give us approx 200 positive mutations over 10 seconds. 
Thus, this would give the expected 200% performance.

BUT:

We are NOT rendering 50 polygons per core in this case.
Each core is only rendering 25 polygons each.

During those 10 seconds, we are actually able to run 2000 generations instead of 1000 per core, thus, running a total of 4000 generations over 10 sec.
Which in turn results in approx 400 positive mutations during the same time span.
**
We have doubled the CPU capacity and halved the work that needs to be done per node.
Thus, we get a * 2 * 2 perf boost.**

Pretty slick 🙂

PS.
The 4 core machine was able to render the Mona Lisa image with the same quality as the last image in the evolution series in: 1 min 34 sec!

//Roger