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bluntman

SSE enhanced fractal noise library.

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rumble -
No I haven't tried a GPU version, my general usage pattern for this library is real-time generation of geometry, and my GPU is already loaded down pretty heavily drawing said geometry! But I will try it at some point.
Andy -
From what I can make out, performing float operations during an SSE task causes the processor to switch from SSE mode to FP mode. Is this correct? So far I have found that anywhere I use a float variable it will cause the next SSE operation to produce indefinite or NaN results.
Yes Core 2 Duos far out perform Pentium D's so I'm sure its not your algorithm that is at fault!
As far as enabling SSE2 making my C++ version run slower I have no idea, but its definitly happening! I have had problems in the past with enabling SSE2 causing projects to crash when they otherwise would not with either SSE1 or no extensions. The final speed figures I quoted were the optimal ones I could get from MSVC2005 sp1 which was using:
Optimization : Maximize Speed
Inline : Any suitable
Favor : Fast Code
Enhanced instruction set: Not set/SSE1 (no difference)

/edit
Just thought I would leave a note here to say that the remainder part of the calculation was bugged, I have fixed this, along with all the type cast warnings and uploaded a new version under the same file name, so the above link will still work.

[Edited by - bluntman on June 17, 2008 8:13:06 PM]

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Hi bluntman,

Thanks for this post, this sample runs a treat here ! I tried it on a grid's vertices positions.

As you posted in 2008, do you know any faster alternative nowadays ?
If yes, could you provide a link or method keyword ?

I am asking because I am testing it on various heavy streams. Of course, I would like to noise as much as possible data so it would be great for me to make sure there is nothing faster out there.

According to you, what would be the fastest coherent 2d/3d fractal noise approach ever so far ? I am probably mistaken but it seems that improved perlin is still on top of things as far as we need 2d or 3d.

Much thanks again for the fantastic sample.

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