⭐ Merited by Cricktor (1)
I'm not soo deep in the technicalities of the method using Kangaroos. Do you (or anybody else) mind explaining in more or less short words why there's such a significant penalty by splitting the range? I struggle a bit at the moment to wrap my head around for an explanation.
If that's is so, than splitting the range to distribute work to multiple GPUs seems not the time and energy efficient way. What's the more efficient work load distribution method? Distributing the number of Kangaroos over multiple GPUs all working on the same range? How to sync efficiently?
If that's is so, than splitting the range to distribute work to multiple GPUs seems not the time and energy efficient way. What's the more efficient work load distribution method? Distributing the number of Kangaroos over multiple GPUs all working on the same range? How to sync efficiently?
Because if you need c*sqrt(n) steps to solve for an n-interval, you need sqrt(2)*c*sqrt(n) to solve for two n/2-intervals. That's an 41% increase in the time to solve, for every halving. It's actually the most efficient way to intentionally increase the necessary number of steps - splitting a problem in two halves until there's nothing more to split
It's basically moving an sqrt(n) complexity problem towards an (n) complexity problem (brute-force).