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Improving the fast inverse square root (2010)

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Re: Improving the fast inverse square root (2010)

#4

That's great and all, but nobody needs a 32-bit anything in 2018. This undergraduate paper provides a magic number and associated error bound for 64-bit doubles: https://cs.uwaterloo.ca/~m32rober/rsqrt.pdf

TIL, no one in the gaming industry uses 32 bit floats any longer. /s

Re: Improving the fast inverse square root (2010)

#5

That's great and all, but nobody needs a 32-bit anything in 2018. This undergraduate paper provides a magic number and associated error bound for 64-bit doubles: https://cs.uwaterloo.ca/~m32rober/rsqrt.pdf

This is not true. In games 32-bit floats are extremely common.

Re: Improving the fast inverse square root (2010)

#6

That's great and all, but nobody needs a 32-bit anything in 2018. This undergraduate paper provides a magic number and associated error bound for 64-bit doubles: https://cs.uwaterloo.ca/~m32rober/rsqrt.pdf

Realtime 3D still uses floats, but only when we can afford something so big, s10e5 is better where available.

Re: Improving the fast inverse square root (2010)

#7

That's great and all, but nobody needs a 32-bit anything in 2018. This undergraduate paper provides a magic number and associated error bound for 64-bit doubles: https://cs.uwaterloo.ca/~m32rober/rsqrt.pdf

deep learning uses low precision floats

sometimes as few as 8 bits are needed

Re: Improving the fast inverse square root (2010)

#8

That's great and all, but nobody needs a 32-bit anything in 2018. This undergraduate paper provides a magic number and associated error bound for 64-bit doubles: https://cs.uwaterloo.ca/~m32rober/rsqrt.pdf

That's not really accurate. Even in cases were 32 bit and 64 bit operations are equally fast on the CPU, 32 bit values still take up half the memory. For many workloads, the limiting factor is cache space. So, if you can use 32 but values, you can get much better performance for those workloads.

Re: Improving the fast inverse square root (2010)

#10

That's great and all, but nobody needs a 32-bit anything in 2018. This undergraduate paper provides a magic number and associated error bound for 64-bit doubles: https://cs.uwaterloo.ca/~m32rober/rsqrt.pdf

Even scientific calculation would be fine with 32 bit floats, but average floating point error due to representation creeps with ON (iirc) over N multiplications, so you have to use 64 bit for many scientific applications to get satisfactory results after a million or a trillion multiplications.
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