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So in the end, if we want to calculate a 1000 x 1000 square, we would need to calculate ~1,000,000 children. If we run with 256 threads, then we need to calculate ~10 generations (I think I did the math wrong here), which would mean we need to count through 0_000_000_000 in base4 space. Each element represents another possible function choice of the IFS and represents another operation of a specific function.
The idea would be to (using notation introduced in #24):
Determine the number of generations we need to generate
This can be easily super-sampled by taking 1 generation more, which would mean smear frames on the new FractalLayer will still appear clean and not grainy
Figure out where in counting space each thread is
Give each thread that offset and then a number to count to and calculate the new point positions assigned to it
Note that this means some threads may have to do a lot more computation than other threads
Maybe offset this by somehow shuffling the counting array? That could cause undue warp divergence...
I think the best approach for certain objects will actually be to do a counting-based solution as was described here: https://www.youtube.com/watch?v=OjTwzFzxR8M
So in the end, if we want to calculate a 1000 x 1000 square, we would need to calculate ~1,000,000 children. If we run with 256 threads, then we need to calculate ~10 generations (I think I did the math wrong here), which would mean we need to count through 0_000_000_000 in base4 space. Each element represents another possible function choice of the IFS and represents another operation of a specific function.
The idea would be to (using notation introduced in #24):
FractalLayer
will still appear clean and not grainyHere's the plan, so far, (#29):
final
/post
Hutchinson operators via counting through fid. This sets the framework for countingThe text was updated successfully, but these errors were encountered: