[noduerme]

Abstractly, when any parallel system scales up large enough without cross checking or waiting between "threads", the cost of de-duplicating and merging the output will probably outweigh the advantage of producing new results in tandem. I think. That's just a hypothesis, but feels correct. With stuff like a-life distributed over lots of servers all converging on evolutionary answers to a problem, it's the collation and analysis layer that's most expensive and slow. Sharing more frequently / allowing more reliance on central historical truth slows each one down but avoids duplication and redundancy. I guess where that point is depends on what problem you're trying to solve.