Disney BSSRDF, sample scattering profile, upper

Percentage Accurate: 95.8% → 98.4%
Time: 10.6s
Alternatives: 7
Speedup: 1.2×

Specification

?
\[\left(0 \leq s \land s \leq 256\right) \land \left(0.25 \leq u \land u \leq 1\right)\]
\[\begin{array}{l} \\ \left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right) \end{array} \]
(FPCore (s u)
 :precision binary32
 (* (* 3.0 s) (log (/ 1.0 (- 1.0 (/ (- u 0.25) 0.75))))))
float code(float s, float u) {
	return (3.0f * s) * logf((1.0f / (1.0f - ((u - 0.25f) / 0.75f))));
}
real(4) function code(s, u)
    real(4), intent (in) :: s
    real(4), intent (in) :: u
    code = (3.0e0 * s) * log((1.0e0 / (1.0e0 - ((u - 0.25e0) / 0.75e0))))
end function
function code(s, u)
	return Float32(Float32(Float32(3.0) * s) * log(Float32(Float32(1.0) / Float32(Float32(1.0) - Float32(Float32(u - Float32(0.25)) / Float32(0.75))))))
end
function tmp = code(s, u)
	tmp = (single(3.0) * s) * log((single(1.0) / (single(1.0) - ((u - single(0.25)) / single(0.75)))));
end
\begin{array}{l}

\\
\left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right)
\end{array}

Sampling outcomes in binary32 precision:

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 7 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 95.8% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right) \end{array} \]
(FPCore (s u)
 :precision binary32
 (* (* 3.0 s) (log (/ 1.0 (- 1.0 (/ (- u 0.25) 0.75))))))
float code(float s, float u) {
	return (3.0f * s) * logf((1.0f / (1.0f - ((u - 0.25f) / 0.75f))));
}
real(4) function code(s, u)
    real(4), intent (in) :: s
    real(4), intent (in) :: u
    code = (3.0e0 * s) * log((1.0e0 / (1.0e0 - ((u - 0.25e0) / 0.75e0))))
end function
function code(s, u)
	return Float32(Float32(Float32(3.0) * s) * log(Float32(Float32(1.0) / Float32(Float32(1.0) - Float32(Float32(u - Float32(0.25)) / Float32(0.75))))))
end
function tmp = code(s, u)
	tmp = (single(3.0) * s) * log((single(1.0) / (single(1.0) - ((u - single(0.25)) / single(0.75)))));
end
\begin{array}{l}

\\
\left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right)
\end{array}

Alternative 1: 98.4% accurate, 0.6× speedup?

\[\begin{array}{l} \\ s \cdot \mathsf{fma}\left(3, \mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right), -3 \cdot \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \mathsf{fma}\left(u, 1.7777777777777777, -0.4444444444444444\right)\right)\right) \end{array} \]
(FPCore (s u)
 :precision binary32
 (*
  s
  (fma
   3.0
   (log1p (fma u 1.3333333333333333 -0.3333333333333333))
   (*
    -3.0
    (log1p (* (- 0.25 u) (fma u 1.7777777777777777 -0.4444444444444444)))))))
float code(float s, float u) {
	return s * fmaf(3.0f, log1pf(fmaf(u, 1.3333333333333333f, -0.3333333333333333f)), (-3.0f * log1pf(((0.25f - u) * fmaf(u, 1.7777777777777777f, -0.4444444444444444f)))));
}
function code(s, u)
	return Float32(s * fma(Float32(3.0), log1p(fma(u, Float32(1.3333333333333333), Float32(-0.3333333333333333))), Float32(Float32(-3.0) * log1p(Float32(Float32(Float32(0.25) - u) * fma(u, Float32(1.7777777777777777), Float32(-0.4444444444444444)))))))
end
\begin{array}{l}

\\
s \cdot \mathsf{fma}\left(3, \mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right), -3 \cdot \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \mathsf{fma}\left(u, 1.7777777777777777, -0.4444444444444444\right)\right)\right)
\end{array}
Derivation
  1. Initial program 96.1%

    \[\left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right) \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-log.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \color{blue}{\log \left(\frac{1}{1 - \frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)} \]
    2. lift-/.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \log \color{blue}{\left(\frac{1}{1 - \frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)} \]
    3. lift--.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \log \left(\frac{1}{\color{blue}{1 - \frac{u - \frac{1}{4}}{\frac{3}{4}}}}\right) \]
    4. flip--N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \log \left(\frac{1}{\color{blue}{\frac{1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}}{1 + \frac{u - \frac{1}{4}}{\frac{3}{4}}}}}\right) \]
    5. clear-numN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \log \color{blue}{\left(\frac{1 + \frac{u - \frac{1}{4}}{\frac{3}{4}}}{1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)} \]
    6. log-divN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \color{blue}{\left(\log \left(1 + \frac{u - \frac{1}{4}}{\frac{3}{4}}\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right)} \]
    7. lower--.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \color{blue}{\left(\log \left(1 + \frac{u - \frac{1}{4}}{\frac{3}{4}}\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right)} \]
    8. lower-log1p.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\color{blue}{\mathsf{log1p}\left(\frac{u - \frac{1}{4}}{\frac{3}{4}}\right)} - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    9. lift-/.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\color{blue}{\frac{u - \frac{1}{4}}{\frac{3}{4}}}\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    10. lift--.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\frac{\color{blue}{u - \frac{1}{4}}}{\frac{3}{4}}\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    11. div-subN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\color{blue}{\frac{u}{\frac{3}{4}} - \frac{\frac{1}{4}}{\frac{3}{4}}}\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    12. sub-negN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\color{blue}{\frac{u}{\frac{3}{4}} + \left(\mathsf{neg}\left(\frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)}\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    13. div-invN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\color{blue}{u \cdot \frac{1}{\frac{3}{4}}} + \left(\mathsf{neg}\left(\frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    14. lower-fma.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\color{blue}{\mathsf{fma}\left(u, \frac{1}{\frac{3}{4}}, \mathsf{neg}\left(\frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)}\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    15. metadata-evalN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\mathsf{fma}\left(u, \color{blue}{\frac{4}{3}}, \mathsf{neg}\left(\frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    16. metadata-evalN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \mathsf{neg}\left(\color{blue}{\frac{1}{3}}\right)\right)\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
    17. metadata-evalN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \color{blue}{\frac{-1}{3}}\right)\right) - \log \left(1 \cdot 1 - \frac{u - \frac{1}{4}}{\frac{3}{4}} \cdot \frac{u - \frac{1}{4}}{\frac{3}{4}}\right)\right) \]
  4. Applied rewrites98.2%

    \[\leadsto \left(3 \cdot s\right) \cdot \color{blue}{\left(\mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right) - \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \left(1.7777777777777777 \cdot \left(u + -0.25\right)\right)\right)\right)} \]
  5. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \color{blue}{\left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right) - \mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right)\right)\right)} \]
    2. lift--.f32N/A

      \[\leadsto \left(3 \cdot s\right) \cdot \color{blue}{\left(\mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right) - \mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right)\right)\right)} \]
    3. sub-negN/A

      \[\leadsto \left(3 \cdot s\right) \cdot \color{blue}{\left(\mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right) + \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right)\right)\right)\right)\right)} \]
    4. distribute-lft-inN/A

      \[\leadsto \color{blue}{\left(3 \cdot s\right) \cdot \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right) + \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right)\right)\right)\right)} \]
    5. lower-fma.f32N/A

      \[\leadsto \color{blue}{\mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right)\right)\right)\right)\right)} \]
    6. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \color{blue}{\left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right)\right)\right)\right)}\right) \]
    7. lower-neg.f3298.3

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right), \left(3 \cdot s\right) \cdot \color{blue}{\left(-\mathsf{log1p}\left(\left(0.25 - u\right) \cdot \left(1.7777777777777777 \cdot \left(u + -0.25\right)\right)\right)\right)}\right) \]
    8. lift-*.f32N/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\color{blue}{\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right)}\right)\right)\right)\right) \]
    9. *-commutativeN/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\color{blue}{\left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right) \cdot \left(\frac{1}{4} - u\right)}\right)\right)\right)\right) \]
    10. lift--.f32N/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right) \cdot \color{blue}{\left(\frac{1}{4} - u\right)}\right)\right)\right)\right) \]
    11. sub-negN/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right) \cdot \color{blue}{\left(\frac{1}{4} + \left(\mathsf{neg}\left(u\right)\right)\right)}\right)\right)\right)\right) \]
    12. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right) \cdot \left(\color{blue}{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)} + \left(\mathsf{neg}\left(u\right)\right)\right)\right)\right)\right)\right) \]
    13. distribute-neg-inN/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right) \cdot \color{blue}{\left(\mathsf{neg}\left(\left(\frac{-1}{4} + u\right)\right)\right)}\right)\right)\right)\right) \]
    14. +-commutativeN/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right) \cdot \left(\mathsf{neg}\left(\color{blue}{\left(u + \frac{-1}{4}\right)}\right)\right)\right)\right)\right)\right) \]
    15. lift-+.f32N/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right) \cdot \left(\mathsf{neg}\left(\color{blue}{\left(u + \frac{-1}{4}\right)}\right)\right)\right)\right)\right)\right) \]
    16. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right), \left(3 \cdot s\right) \cdot \left(\mathsf{neg}\left(\mathsf{log1p}\left(\color{blue}{\left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right) \cdot \left(\mathsf{neg}\left(\left(u + \frac{-1}{4}\right)\right)\right)}\right)\right)\right)\right) \]
  6. Applied rewrites98.3%

    \[\leadsto \color{blue}{\mathsf{fma}\left(3 \cdot s, \mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right), \left(3 \cdot s\right) \cdot \left(-\mathsf{log1p}\left(\mathsf{fma}\left(1.7777777777777777, u, -0.4444444444444444\right) \cdot \left(0.25 - u\right)\right)\right)\right)} \]
  7. Taylor expanded in s around 0

    \[\leadsto \color{blue}{s \cdot \left(-3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right) + 3 \cdot \log \left(\frac{2}{3} + \frac{4}{3} \cdot u\right)\right)} \]
  8. Step-by-step derivation
    1. lower-*.f32N/A

      \[\leadsto \color{blue}{s \cdot \left(-3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right) + 3 \cdot \log \left(\frac{2}{3} + \frac{4}{3} \cdot u\right)\right)} \]
    2. +-commutativeN/A

      \[\leadsto s \cdot \color{blue}{\left(3 \cdot \log \left(\frac{2}{3} + \frac{4}{3} \cdot u\right) + -3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)\right)} \]
    3. lower-fma.f32N/A

      \[\leadsto s \cdot \color{blue}{\mathsf{fma}\left(3, \log \left(\frac{2}{3} + \frac{4}{3} \cdot u\right), -3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)\right)} \]
    4. lower-log.f32N/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \color{blue}{\log \left(\frac{2}{3} + \frac{4}{3} \cdot u\right)}, -3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)\right) \]
    5. +-commutativeN/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \color{blue}{\left(\frac{4}{3} \cdot u + \frac{2}{3}\right)}, -3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)\right) \]
    6. *-commutativeN/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\color{blue}{u \cdot \frac{4}{3}} + \frac{2}{3}\right), -3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)\right) \]
    7. lower-fma.f32N/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \color{blue}{\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{2}{3}\right)\right)}, -3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)\right) \]
    8. lower-*.f32N/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{2}{3}\right)\right), \color{blue}{-3 \cdot \log \left(1 + \left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)}\right) \]
    9. lower-log1p.f32N/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{2}{3}\right)\right), -3 \cdot \color{blue}{\mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)}\right) \]
    10. lower-*.f32N/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{2}{3}\right)\right), -3 \cdot \mathsf{log1p}\left(\color{blue}{\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)}\right)\right) \]
    11. lower--.f32N/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{2}{3}\right)\right), -3 \cdot \mathsf{log1p}\left(\color{blue}{\left(\frac{1}{4} - u\right)} \cdot \left(\frac{16}{9} \cdot u - \frac{4}{9}\right)\right)\right) \]
    12. sub-negN/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{2}{3}\right)\right), -3 \cdot \mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \color{blue}{\left(\frac{16}{9} \cdot u + \left(\mathsf{neg}\left(\frac{4}{9}\right)\right)\right)}\right)\right) \]
    13. *-commutativeN/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{2}{3}\right)\right), -3 \cdot \mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\color{blue}{u \cdot \frac{16}{9}} + \left(\mathsf{neg}\left(\frac{4}{9}\right)\right)\right)\right)\right) \]
    14. lower-fma.f32N/A

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{2}{3}\right)\right), -3 \cdot \mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \color{blue}{\mathsf{fma}\left(u, \frac{16}{9}, \mathsf{neg}\left(\frac{4}{9}\right)\right)}\right)\right) \]
    15. metadata-eval96.0

      \[\leadsto s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, 1.3333333333333333, 0.6666666666666666\right)\right), -3 \cdot \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \mathsf{fma}\left(u, 1.7777777777777777, \color{blue}{-0.4444444444444444}\right)\right)\right) \]
  9. Applied rewrites96.0%

    \[\leadsto \color{blue}{s \cdot \mathsf{fma}\left(3, \log \left(\mathsf{fma}\left(u, 1.3333333333333333, 0.6666666666666666\right)\right), -3 \cdot \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \mathsf{fma}\left(u, 1.7777777777777777, -0.4444444444444444\right)\right)\right)} \]
  10. Step-by-step derivation
    1. Applied rewrites98.5%

      \[\leadsto \mathsf{fma}\left(3, \mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right), -3 \cdot \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \mathsf{fma}\left(u, 1.7777777777777777, -0.4444444444444444\right)\right)\right) \cdot \color{blue}{s} \]
    2. Final simplification98.5%

      \[\leadsto s \cdot \mathsf{fma}\left(3, \mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right), -3 \cdot \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \mathsf{fma}\left(u, 1.7777777777777777, -0.4444444444444444\right)\right)\right) \]
    3. Add Preprocessing

    Alternative 2: 98.3% accurate, 1.1× speedup?

    \[\begin{array}{l} \\ 3 \cdot \left(\left(-s\right) \cdot \mathsf{log1p}\left(\frac{0.25 - u}{0.75}\right)\right) \end{array} \]
    (FPCore (s u)
     :precision binary32
     (* 3.0 (* (- s) (log1p (/ (- 0.25 u) 0.75)))))
    float code(float s, float u) {
    	return 3.0f * (-s * log1pf(((0.25f - u) / 0.75f)));
    }
    
    function code(s, u)
    	return Float32(Float32(3.0) * Float32(Float32(-s) * log1p(Float32(Float32(Float32(0.25) - u) / Float32(0.75)))))
    end
    
    \begin{array}{l}
    
    \\
    3 \cdot \left(\left(-s\right) \cdot \mathsf{log1p}\left(\frac{0.25 - u}{0.75}\right)\right)
    \end{array}
    
    Derivation
    1. Initial program 95.8%

      \[\left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f32N/A

        \[\leadsto \color{blue}{\left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)} \]
      2. lift-*.f32N/A

        \[\leadsto \color{blue}{\left(3 \cdot s\right)} \cdot \log \left(\frac{1}{1 - \frac{u - \frac{1}{4}}{\frac{3}{4}}}\right) \]
      3. associate-*l*N/A

        \[\leadsto \color{blue}{3 \cdot \left(s \cdot \log \left(\frac{1}{1 - \frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)\right)} \]
      4. *-commutativeN/A

        \[\leadsto \color{blue}{\left(s \cdot \log \left(\frac{1}{1 - \frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)\right) \cdot 3} \]
      5. lower-*.f32N/A

        \[\leadsto \color{blue}{\left(s \cdot \log \left(\frac{1}{1 - \frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)\right) \cdot 3} \]
    4. Applied rewrites97.9%

      \[\leadsto \color{blue}{\left(\left(-s\right) \cdot \mathsf{log1p}\left(-\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right)\right) \cdot 3} \]
    5. Step-by-step derivation
      1. lift-neg.f32N/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\color{blue}{\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)}\right)\right) \cdot 3 \]
      2. lift-fma.f32N/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\color{blue}{\left(u \cdot \frac{4}{3} + \frac{-1}{3}\right)}\right)\right)\right) \cdot 3 \]
      3. metadata-evalN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\left(u \cdot \frac{4}{3} + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{3}\right)\right)}\right)\right)\right)\right) \cdot 3 \]
      4. metadata-evalN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\left(u \cdot \frac{4}{3} + \left(\mathsf{neg}\left(\color{blue}{\frac{\frac{1}{4}}{\frac{3}{4}}}\right)\right)\right)\right)\right)\right) \cdot 3 \]
      5. sub-negN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\color{blue}{\left(u \cdot \frac{4}{3} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)}\right)\right)\right) \cdot 3 \]
      6. metadata-evalN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\left(u \cdot \color{blue}{\frac{1}{\frac{3}{4}}} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)\right)\right) \cdot 3 \]
      7. div-invN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\left(\color{blue}{\frac{u}{\frac{3}{4}}} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)\right)\right) \cdot 3 \]
      8. div-subN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\color{blue}{\frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)\right)\right) \cdot 3 \]
      9. clear-numN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\color{blue}{\frac{1}{\frac{\frac{3}{4}}{u - \frac{1}{4}}}}\right)\right)\right) \cdot 3 \]
      10. clear-numN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\color{blue}{\frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)\right)\right) \cdot 3 \]
      11. sub-negN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\frac{\color{blue}{u + \left(\mathsf{neg}\left(\frac{1}{4}\right)\right)}}{\frac{3}{4}}\right)\right)\right) \cdot 3 \]
      12. metadata-evalN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\frac{u + \color{blue}{\frac{-1}{4}}}{\frac{3}{4}}\right)\right)\right) \cdot 3 \]
      13. lift-+.f32N/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\frac{\color{blue}{u + \frac{-1}{4}}}{\frac{3}{4}}\right)\right)\right) \cdot 3 \]
      14. distribute-neg-fracN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\color{blue}{\frac{\mathsf{neg}\left(\left(u + \frac{-1}{4}\right)\right)}{\frac{3}{4}}}\right)\right) \cdot 3 \]
      15. lower-/.f32N/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\color{blue}{\frac{\mathsf{neg}\left(\left(u + \frac{-1}{4}\right)\right)}{\frac{3}{4}}}\right)\right) \cdot 3 \]
      16. lift-+.f32N/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\frac{\mathsf{neg}\left(\color{blue}{\left(u + \frac{-1}{4}\right)}\right)}{\frac{3}{4}}\right)\right) \cdot 3 \]
      17. +-commutativeN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\frac{\mathsf{neg}\left(\color{blue}{\left(\frac{-1}{4} + u\right)}\right)}{\frac{3}{4}}\right)\right) \cdot 3 \]
      18. distribute-neg-inN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\frac{\color{blue}{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right) + \left(\mathsf{neg}\left(u\right)\right)}}{\frac{3}{4}}\right)\right) \cdot 3 \]
      19. metadata-evalN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\frac{\color{blue}{\frac{1}{4}} + \left(\mathsf{neg}\left(u\right)\right)}{\frac{3}{4}}\right)\right) \cdot 3 \]
      20. sub-negN/A

        \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\frac{\color{blue}{\frac{1}{4} - u}}{\frac{3}{4}}\right)\right) \cdot 3 \]
      21. lift--.f3298.3

        \[\leadsto \left(\left(-s\right) \cdot \mathsf{log1p}\left(\frac{\color{blue}{0.25 - u}}{0.75}\right)\right) \cdot 3 \]
    6. Applied rewrites98.3%

      \[\leadsto \left(\left(-s\right) \cdot \mathsf{log1p}\left(\color{blue}{\frac{0.25 - u}{0.75}}\right)\right) \cdot 3 \]
    7. Final simplification98.3%

      \[\leadsto 3 \cdot \left(\left(-s\right) \cdot \mathsf{log1p}\left(\frac{0.25 - u}{0.75}\right)\right) \]
    8. Add Preprocessing

    Reproduce

    ?
    herbie shell --seed 2024230 
    (FPCore (s u)
      :name "Disney BSSRDF, sample scattering profile, upper"
      :precision binary32
      :pre (and (and (<= 0.0 s) (<= s 256.0)) (and (<= 0.25 u) (<= u 1.0)))
      (* (* 3.0 s) (log (/ 1.0 (- 1.0 (/ (- u 0.25) 0.75))))))