Moshe Looks writes:> This is not quite correct; it really depends on the complexity of the > programs one is evolving and the structure of the fitness function. For > simple cases, it can really rock; see> > http://www.cs.ucl.ac.uk/staff/W.Langdon/ That's interesting work, thanks for the link! It's not immediately obvious, but the particular example there is a population of programs that estimate pi with up to 8 leaves from an "alphabet" of six tokens (2 constants and 4 basic arithmetic operations). The strategy used for parallelization is to run all programs currently waiting on a '+' operation, then run all programs doing a '-' operation and so on. If there are N operations (4 in this case), the population runs at 1/N speed (since the SIMD nature of the thing makes the others wait). So you're right, for simple cases like this one it only wastes 75% of the available processing power. It doesn't seem like it will scale very well though. Even on this simple task I bet a quad-core cpu is competitive with the GPU hardware. It does point out though that some things that are not intuitively data parallel can be executed effectively on a GPU. Do you personally think MOSES will run well on a GPU?
----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=e9e40a7e
