Disney BSSRDF, sample scattering profile, upper

Percentage Accurate: 96.0% → 98.3%
Time: 10.4s
Alternatives: 5
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 5 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: 96.0% 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: 98.3% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\frac{0.25 - u}{-0.75}\right) - \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \left(1.7777777777777777 \cdot \left(u + -0.25\right)\right)\right)\right) \end{array} \]
(FPCore (s u)
 :precision binary32
 (*
  (* 3.0 s)
  (-
   (log1p (/ (- 0.25 u) -0.75))
   (log1p (* (- 0.25 u) (* 1.7777777777777777 (+ u -0.25)))))))
float code(float s, float u) {
	return (3.0f * s) * (log1pf(((0.25f - u) / -0.75f)) - log1pf(((0.25f - u) * (1.7777777777777777f * (u + -0.25f)))));
}
function code(s, u)
	return Float32(Float32(Float32(3.0) * s) * Float32(log1p(Float32(Float32(Float32(0.25) - u) / Float32(-0.75))) - log1p(Float32(Float32(Float32(0.25) - u) * Float32(Float32(1.7777777777777777) * Float32(u + Float32(-0.25)))))))
end
\begin{array}{l}

\\
\left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\frac{0.25 - u}{-0.75}\right) - \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \left(1.7777777777777777 \cdot \left(u + -0.25\right)\right)\right)\right)
\end{array}
Derivation
  1. Initial program 95.9%

    \[\left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right) \]
  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 rewrites98.3%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\frac{\color{blue}{\frac{1}{4} - u}}{\mathsf{neg}\left(\frac{3}{4}\right)}\right) - \mathsf{log1p}\left(\left(\frac{1}{4} - u\right) \cdot \left(\frac{16}{9} \cdot \left(u + \frac{-1}{4}\right)\right)\right)\right) \]
    17. metadata-eval98.6

      \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\frac{0.25 - u}{\color{blue}{-0.75}}\right) - \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \left(1.7777777777777777 \cdot \left(u + -0.25\right)\right)\right)\right) \]
  6. Applied rewrites98.6%

    \[\leadsto \left(3 \cdot s\right) \cdot \left(\mathsf{log1p}\left(\color{blue}{\frac{0.25 - u}{-0.75}}\right) - \mathsf{log1p}\left(\left(0.25 - u\right) \cdot \left(1.7777777777777777 \cdot \left(u + -0.25\right)\right)\right)\right) \]
  7. Add Preprocessing

Alternative 2: 98.3% accurate, 1.1× speedup?

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

\\
s \cdot \left(-3 \cdot \mathsf{log1p}\left(\frac{0.25 - u}{0.75}\right)\right)
\end{array}
Derivation
  1. Initial program 95.9%

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

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

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

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

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

      \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(\color{blue}{\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)}\right)\right) \cdot s \]
    2. neg-sub0N/A

      \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(\color{blue}{0 - \mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)}\right)\right) \cdot s \]
    3. lift-fma.f32N/A

      \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(0 - \color{blue}{\left(u \cdot \frac{4}{3} + \frac{-1}{3}\right)}\right)\right) \cdot s \]
    4. +-commutativeN/A

      \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(0 - \color{blue}{\left(\frac{-1}{3} + u \cdot \frac{4}{3}\right)}\right)\right) \cdot s \]
    5. associate--r+N/A

      \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(\color{blue}{\left(0 - \frac{-1}{3}\right) - u \cdot \frac{4}{3}}\right)\right) \cdot s \]
    6. metadata-evalN/A

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

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

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

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

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

      \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(\frac{\color{blue}{\frac{1}{4} - u}}{\frac{3}{4}}\right)\right) \cdot s \]
    12. lower-/.f3298.5

      \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(\color{blue}{\frac{0.25 - u}{0.75}}\right)\right) \cdot s \]
  6. Applied rewrites98.5%

    \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(\color{blue}{\frac{0.25 - u}{0.75}}\right)\right) \cdot s \]
  7. Final simplification98.5%

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

Alternative 3: 97.9% accurate, 1.2× speedup?

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

\\
s \cdot \left(-3 \cdot \mathsf{log1p}\left(\mathsf{fma}\left(u, -1.3333333333333333, 0.3333333333333333\right)\right)\right)
\end{array}
Derivation
  1. Initial program 95.9%

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(\color{blue}{\mathsf{fma}\left(u, -1.3333333333333333, 0.3333333333333333\right)}\right)\right) \cdot s \]
  6. Applied rewrites98.1%

    \[\leadsto \left(-3 \cdot \mathsf{log1p}\left(\color{blue}{\mathsf{fma}\left(u, -1.3333333333333333, 0.3333333333333333\right)}\right)\right) \cdot s \]
  7. Final simplification98.1%

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

Alternative 4: 97.9% accurate, 1.2× speedup?

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

\\
\left(s \cdot -3\right) \cdot \mathsf{log1p}\left(\mathsf{fma}\left(-1.3333333333333333, u, 0.3333333333333333\right)\right)
\end{array}
Derivation
  1. Initial program 95.9%

    \[\left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right) \]
  2. Add Preprocessing
  3. Taylor expanded in s around 0

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

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

      \[\leadsto \left(3 \cdot s\right) \cdot \color{blue}{\left(\mathsf{neg}\left(\log \left(1 - \frac{4}{3} \cdot \left(u - \frac{1}{4}\right)\right)\right)\right)} \]
    3. distribute-rgt-neg-outN/A

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \left(s \cdot -3\right) \cdot \mathsf{log1p}\left(\color{blue}{\mathsf{fma}\left(-1.3333333333333333, u, 0.3333333333333333\right)}\right) \]
  5. Applied rewrites98.1%

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

Alternative 5: 30.0% accurate, 10.7× speedup?

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

\\
s \cdot \left(-3 \cdot \left(-u\right)\right)
\end{array}
Derivation
  1. Initial program 95.9%

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

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

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

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

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

    \[\leadsto \left(-3 \cdot \color{blue}{\left(\log \frac{4}{3} + -1 \cdot u\right)}\right) \cdot s \]
  6. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto \left(-3 \cdot \left(\log \frac{4}{3} + \color{blue}{\left(\mathsf{neg}\left(u\right)\right)}\right)\right) \cdot s \]
    2. unsub-negN/A

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

      \[\leadsto \left(-3 \cdot \color{blue}{\left(\log \frac{4}{3} - u\right)}\right) \cdot s \]
    4. lower-log.f3225.8

      \[\leadsto \left(-3 \cdot \left(\color{blue}{\log 1.3333333333333333} - u\right)\right) \cdot s \]
  7. Applied rewrites25.8%

    \[\leadsto \left(-3 \cdot \color{blue}{\left(\log 1.3333333333333333 - u\right)}\right) \cdot s \]
  8. Taylor expanded in u around inf

    \[\leadsto \left(-3 \cdot \left(-1 \cdot \color{blue}{u}\right)\right) \cdot s \]
  9. Step-by-step derivation
    1. Applied rewrites29.9%

      \[\leadsto \left(-3 \cdot \left(-u\right)\right) \cdot s \]
    2. Final simplification29.9%

      \[\leadsto s \cdot \left(-3 \cdot \left(-u\right)\right) \]
    3. Add Preprocessing

    Reproduce

    ?
    herbie shell --seed 2024233 
    (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))))))