Quote:
Originally Posted by Dark Shikari
Incorrect. The specification requires bit-exact decoding or decoder/encoder desync will occur, resulting in artifacts.
|
Okay, so it's a "cleanup" cycle in decoding. Too bad, I had hoped for sine-wave-like transformations and convolution like with lossy audio that does benefit from floating-points.
Quote:
Originally Posted by Dark Shikari
SSE is part of the FPU. It shares the same execution units.
|
I mostly meant relying on the classical 1-level approach, instead of 2 or more SIMD instructions at a time.
Quote:
Originally Posted by Dark Shikari
This isn't even considering the fact that integer math allows all sorts of useful shortcuts, like shifting instead of multiplication, bitmasking, and other performance tricks which are often impossible with floating point math.
|
Bitmasking and such is indeed tricky on floating-points. I've done some on GPU work, and I can say that the bit field in floating-point mode is too variable to pull it off correctly usually. Only sign and some exponent tricks work well bit-wise.
The fact that I need to rely more and more on doubles and some floats for various things, does decrease my usage of bitmasking and such. The SSE example shows how to get at least some decent performance on doubles and floats on a CPU. (And give at least some impression to what it is for the regular people here.)