Disney BSSRDF, PDF of scattering profile

Percentage Accurate: 99.6% → 99.6%
Time: 14.9s
Alternatives: 15
Speedup: 1.0×

Specification

?
\[\left(0 \leq s \land s \leq 256\right) \land \left(10^{-6} < r \land r < 1000000\right)\]
\[\begin{array}{l} \\ \frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* 0.25 (exp (/ (- r) s))) (* (* (* 2.0 PI) s) r))
  (/ (* 0.75 (exp (/ (- r) (* 3.0 s)))) (* (* (* 6.0 PI) s) r))))
float code(float s, float r) {
	return ((0.25f * expf((-r / s))) / (((2.0f * ((float) M_PI)) * s) * r)) + ((0.75f * expf((-r / (3.0f * s)))) / (((6.0f * ((float) M_PI)) * s) * r));
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.25) * exp(Float32(Float32(-r) / s))) / Float32(Float32(Float32(Float32(2.0) * Float32(pi)) * s) * r)) + Float32(Float32(Float32(0.75) * exp(Float32(Float32(-r) / Float32(Float32(3.0) * s)))) / Float32(Float32(Float32(Float32(6.0) * Float32(pi)) * s) * r)))
end
function tmp = code(s, r)
	tmp = ((single(0.25) * exp((-r / s))) / (((single(2.0) * single(pi)) * s) * r)) + ((single(0.75) * exp((-r / (single(3.0) * s)))) / (((single(6.0) * single(pi)) * s) * r));
end
\begin{array}{l}

\\
\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r}
\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 15 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: 99.6% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* 0.25 (exp (/ (- r) s))) (* (* (* 2.0 PI) s) r))
  (/ (* 0.75 (exp (/ (- r) (* 3.0 s)))) (* (* (* 6.0 PI) s) r))))
float code(float s, float r) {
	return ((0.25f * expf((-r / s))) / (((2.0f * ((float) M_PI)) * s) * r)) + ((0.75f * expf((-r / (3.0f * s)))) / (((6.0f * ((float) M_PI)) * s) * r));
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.25) * exp(Float32(Float32(-r) / s))) / Float32(Float32(Float32(Float32(2.0) * Float32(pi)) * s) * r)) + Float32(Float32(Float32(0.75) * exp(Float32(Float32(-r) / Float32(Float32(3.0) * s)))) / Float32(Float32(Float32(Float32(6.0) * Float32(pi)) * s) * r)))
end
function tmp = code(s, r)
	tmp = ((single(0.25) * exp((-r / s))) / (((single(2.0) * single(pi)) * s) * r)) + ((single(0.75) * exp((-r / (single(3.0) * s)))) / (((single(6.0) * single(pi)) * s) * r));
end
\begin{array}{l}

\\
\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r}
\end{array}

Alternative 1: 99.6% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{0.125 \cdot e^{\frac{r}{-s}}}{r \cdot \left(s \cdot \pi\right)} + \frac{\frac{0.75 \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\pi}}{s \cdot 6} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* 0.125 (exp (/ r (- s)))) (* r (* s PI)))
  (/ (/ (* 0.75 (/ (exp (/ r (* s -3.0))) r)) PI) (* s 6.0))))
float code(float s, float r) {
	return ((0.125f * expf((r / -s))) / (r * (s * ((float) M_PI)))) + (((0.75f * (expf((r / (s * -3.0f))) / r)) / ((float) M_PI)) / (s * 6.0f));
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.125) * exp(Float32(r / Float32(-s)))) / Float32(r * Float32(s * Float32(pi)))) + Float32(Float32(Float32(Float32(0.75) * Float32(exp(Float32(r / Float32(s * Float32(-3.0)))) / r)) / Float32(pi)) / Float32(s * Float32(6.0))))
end
function tmp = code(s, r)
	tmp = ((single(0.125) * exp((r / -s))) / (r * (s * single(pi)))) + (((single(0.75) * (exp((r / (s * single(-3.0)))) / r)) / single(pi)) / (s * single(6.0)));
end
\begin{array}{l}

\\
\frac{0.125 \cdot e^{\frac{r}{-s}}}{r \cdot \left(s \cdot \pi\right)} + \frac{\frac{0.75 \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\pi}}{s \cdot 6}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{3}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{\left(\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r}} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\color{blue}{\frac{3}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}}{\left(\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{\color{blue}{\left(\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r}} \]
    4. times-fracN/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{3}{4}}{\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}} \]
    5. associate-*l/N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s}} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\color{blue}{\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s}} \]
    7. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\color{blue}{\left(6 \cdot \mathsf{PI}\left(\right)\right)} \cdot s} \]
    8. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot 6\right)} \cdot s} \]
    9. associate-*l*N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\color{blue}{\mathsf{PI}\left(\right) \cdot \left(6 \cdot s\right)}} \]
    10. associate-/r*N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s}} \]
    11. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s}} \]
  4. Applied rewrites99.5%

    \[\leadsto \frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{0.75 \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\pi}}{6 \cdot s}} \]
  5. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r}} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\color{blue}{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r}} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    4. times-fracN/A

      \[\leadsto \color{blue}{\frac{\frac{1}{4}}{\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r}} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    5. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{\left(2 \cdot \mathsf{PI}\left(\right)\right)} \cdot s} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    7. associate-*l*N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{2 \cdot \left(\mathsf{PI}\left(\right) \cdot s\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    8. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{2 \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    9. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{2 \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    10. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{4}}{2}}{s \cdot \mathsf{PI}\left(\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    11. metadata-evalN/A

      \[\leadsto \frac{\color{blue}{\frac{1}{8}}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    12. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{\color{blue}{\mathsf{neg}\left(r\right)}}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    13. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{\mathsf{neg}\left(r\right)}{s}}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    14. distribute-frac-negN/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\mathsf{neg}\left(\frac{r}{s}\right)}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    15. distribute-frac-neg2N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    16. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\color{blue}{\mathsf{neg}\left(s\right)}}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    17. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
  6. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{0.125 \cdot e^{\frac{r}{-s}}}{r \cdot \left(s \cdot \pi\right)}} + \frac{\frac{0.75 \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\pi}}{6 \cdot s} \]
  7. Final simplification99.5%

    \[\leadsto \frac{0.125 \cdot e^{\frac{r}{-s}}}{r \cdot \left(s \cdot \pi\right)} + \frac{\frac{0.75 \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\pi}}{s \cdot 6} \]
  8. Add Preprocessing

Alternative 2: 99.6% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{e^{\frac{r}{-s}} \cdot 0.25}{r \cdot \left(s \cdot \left(\pi \cdot 2\right)\right)} + \frac{0.75 \cdot e^{\frac{r}{s \cdot \left(-3\right)}}}{r \cdot \left(s \cdot \left(\pi \cdot 6\right)\right)} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* (exp (/ r (- s))) 0.25) (* r (* s (* PI 2.0))))
  (/ (* 0.75 (exp (/ r (* s (- 3.0))))) (* r (* s (* PI 6.0))))))
float code(float s, float r) {
	return ((expf((r / -s)) * 0.25f) / (r * (s * (((float) M_PI) * 2.0f)))) + ((0.75f * expf((r / (s * -3.0f)))) / (r * (s * (((float) M_PI) * 6.0f))));
}
function code(s, r)
	return Float32(Float32(Float32(exp(Float32(r / Float32(-s))) * Float32(0.25)) / Float32(r * Float32(s * Float32(Float32(pi) * Float32(2.0))))) + Float32(Float32(Float32(0.75) * exp(Float32(r / Float32(s * Float32(-Float32(3.0)))))) / Float32(r * Float32(s * Float32(Float32(pi) * Float32(6.0))))))
end
function tmp = code(s, r)
	tmp = ((exp((r / -s)) * single(0.25)) / (r * (s * (single(pi) * single(2.0))))) + ((single(0.75) * exp((r / (s * -single(3.0))))) / (r * (s * (single(pi) * single(6.0)))));
end
\begin{array}{l}

\\
\frac{e^{\frac{r}{-s}} \cdot 0.25}{r \cdot \left(s \cdot \left(\pi \cdot 2\right)\right)} + \frac{0.75 \cdot e^{\frac{r}{s \cdot \left(-3\right)}}}{r \cdot \left(s \cdot \left(\pi \cdot 6\right)\right)}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Add Preprocessing
  3. Final simplification99.5%

    \[\leadsto \frac{e^{\frac{r}{-s}} \cdot 0.25}{r \cdot \left(s \cdot \left(\pi \cdot 2\right)\right)} + \frac{0.75 \cdot e^{\frac{r}{s \cdot \left(-3\right)}}}{r \cdot \left(s \cdot \left(\pi \cdot 6\right)\right)} \]
  4. Add Preprocessing

Alternative 3: 99.5% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \frac{\frac{0.125 \cdot \frac{e^{\frac{r}{-s}} + e^{r \cdot \frac{-0.3333333333333333}{s}}}{r}}{\pi}}{s} \end{array} \]
(FPCore (s r)
 :precision binary32
 (/
  (/
   (* 0.125 (/ (+ (exp (/ r (- s))) (exp (* r (/ -0.3333333333333333 s)))) r))
   PI)
  s))
float code(float s, float r) {
	return ((0.125f * ((expf((r / -s)) + expf((r * (-0.3333333333333333f / s)))) / r)) / ((float) M_PI)) / s;
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.125) * Float32(Float32(exp(Float32(r / Float32(-s))) + exp(Float32(r * Float32(Float32(-0.3333333333333333) / s)))) / r)) / Float32(pi)) / s)
end
function tmp = code(s, r)
	tmp = ((single(0.125) * ((exp((r / -s)) + exp((r * (single(-0.3333333333333333) / s)))) / r)) / single(pi)) / s;
end
\begin{array}{l}

\\
\frac{\frac{0.125 \cdot \frac{e^{\frac{r}{-s}} + e^{r \cdot \frac{-0.3333333333333333}{s}}}{r}}{\pi}}{s}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Add Preprocessing
  3. Applied rewrites99.1%

    \[\leadsto \color{blue}{\frac{0.125}{s \cdot \pi} \cdot \left(\frac{e^{\frac{r}{s \cdot -3}}}{r} + \frac{e^{\frac{r}{-s}}}{r}\right)} \]
  4. Taylor expanded in r around inf

    \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r}} \]
  5. Step-by-step derivation
    1. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r}} \]
    2. lower-+.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{\color{blue}{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}}{r} \]
    3. lower-exp.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{\color{blue}{e^{-1 \cdot \frac{r}{s}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    4. mul-1-negN/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\mathsf{neg}\left(\frac{r}{s}\right)}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    5. distribute-neg-frac2N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    6. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    7. lower-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\color{blue}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    8. lower-exp.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + \color{blue}{e^{\frac{-1}{3} \cdot \frac{r}{s}}}}{r} \]
    9. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\color{blue}{\frac{r}{s} \cdot \frac{-1}{3}}}}{r} \]
    10. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\color{blue}{\frac{r}{s} \cdot \frac{-1}{3}}}}{r} \]
    11. lower-/.f3299.0

      \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + e^{\color{blue}{\frac{r}{s}} \cdot -0.3333333333333333}}{r} \]
  6. Applied rewrites99.0%

    \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \color{blue}{\frac{e^{\frac{r}{-s}} + e^{\frac{r}{s} \cdot -0.3333333333333333}}{r}} \]
  7. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\frac{r}{s} \cdot \frac{-1}{3}}}{r}} \]
    2. lift-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)}} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\frac{r}{s} \cdot \frac{-1}{3}}}{r} \]
    3. associate-*l/N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{8} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\frac{r}{s} \cdot \frac{-1}{3}}}{r}}{s \cdot \mathsf{PI}\left(\right)}} \]
    4. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\frac{r}{s} \cdot \frac{-1}{3}}}{r}}{\color{blue}{s \cdot \mathsf{PI}\left(\right)}} \]
    5. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{8} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\frac{r}{s} \cdot \frac{-1}{3}}}{r}}{\color{blue}{\mathsf{PI}\left(\right) \cdot s}} \]
    6. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{8} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\frac{r}{s} \cdot \frac{-1}{3}}}{r}}{\mathsf{PI}\left(\right)}}{s}} \]
    7. lower-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{8} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\frac{r}{s} \cdot \frac{-1}{3}}}{r}}{\mathsf{PI}\left(\right)}}{s}} \]
  8. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{\frac{0.125 \cdot \frac{e^{\frac{r}{-s}} + e^{r \cdot \frac{-0.3333333333333333}{s}}}{r}}{\pi}}{s}} \]
  9. Add Preprocessing

Alternative 4: 99.5% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \frac{0.125 \cdot \left(e^{\frac{r}{-s}} + e^{-0.3333333333333333 \cdot \frac{r}{s}}\right)}{r \cdot \left(s \cdot \pi\right)} \end{array} \]
(FPCore (s r)
 :precision binary32
 (/
  (* 0.125 (+ (exp (/ r (- s))) (exp (* -0.3333333333333333 (/ r s)))))
  (* r (* s PI))))
float code(float s, float r) {
	return (0.125f * (expf((r / -s)) + expf((-0.3333333333333333f * (r / s))))) / (r * (s * ((float) M_PI)));
}
function code(s, r)
	return Float32(Float32(Float32(0.125) * Float32(exp(Float32(r / Float32(-s))) + exp(Float32(Float32(-0.3333333333333333) * Float32(r / s))))) / Float32(r * Float32(s * Float32(pi))))
end
function tmp = code(s, r)
	tmp = (single(0.125) * (exp((r / -s)) + exp((single(-0.3333333333333333) * (r / s))))) / (r * (s * single(pi)));
end
\begin{array}{l}

\\
\frac{0.125 \cdot \left(e^{\frac{r}{-s}} + e^{-0.3333333333333333 \cdot \frac{r}{s}}\right)}{r \cdot \left(s \cdot \pi\right)}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Add Preprocessing
  3. Applied rewrites99.1%

    \[\leadsto \color{blue}{\frac{0.125}{s \cdot \pi} \cdot \left(\frac{e^{\frac{r}{s \cdot -3}}}{r} + \frac{e^{\frac{r}{-s}}}{r}\right)} \]
  4. Taylor expanded in r around inf

    \[\leadsto \color{blue}{\frac{1}{8} \cdot \frac{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
  5. Step-by-step derivation
    1. associate-*r/N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{8} \cdot \left(e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}\right)}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    2. metadata-evalN/A

      \[\leadsto \frac{\color{blue}{\left(\frac{-1}{8} \cdot -1\right)} \cdot \left(e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}\right)}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)} \]
    3. associate-*r*N/A

      \[\leadsto \frac{\color{blue}{\frac{-1}{8} \cdot \left(-1 \cdot \left(e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}\right)\right)}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)} \]
    4. distribute-lft-outN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \color{blue}{\left(-1 \cdot e^{-1 \cdot \frac{r}{s}} + -1 \cdot e^{\frac{-1}{3} \cdot \frac{r}{s}}\right)}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)} \]
    5. lower-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{-1}{8} \cdot \left(-1 \cdot e^{-1 \cdot \frac{r}{s}} + -1 \cdot e^{\frac{-1}{3} \cdot \frac{r}{s}}\right)}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
  6. Applied rewrites99.4%

    \[\leadsto \color{blue}{\frac{0.125 \cdot \left(e^{\frac{r}{-s}} + e^{\frac{r}{s} \cdot -0.3333333333333333}\right)}{r \cdot \left(s \cdot \pi\right)}} \]
  7. Final simplification99.4%

    \[\leadsto \frac{0.125 \cdot \left(e^{\frac{r}{-s}} + e^{-0.3333333333333333 \cdot \frac{r}{s}}\right)}{r \cdot \left(s \cdot \pi\right)} \]
  8. Add Preprocessing

Alternative 5: 10.7% accurate, 1.3× speedup?

\[\begin{array}{l} \\ \frac{e^{\frac{r}{-s}} \cdot 0.25}{r \cdot \left(s \cdot \left(\pi \cdot 2\right)\right)} + \frac{\frac{0.125}{r \cdot \pi} + \mathsf{fma}\left(r, \frac{0.006944444444444444}{s \cdot \left(s \cdot \pi\right)}, \frac{-0.041666666666666664}{s \cdot \pi}\right)}{s} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* (exp (/ r (- s))) 0.25) (* r (* s (* PI 2.0))))
  (/
   (+
    (/ 0.125 (* r PI))
    (fma
     r
     (/ 0.006944444444444444 (* s (* s PI)))
     (/ -0.041666666666666664 (* s PI))))
   s)))
float code(float s, float r) {
	return ((expf((r / -s)) * 0.25f) / (r * (s * (((float) M_PI) * 2.0f)))) + (((0.125f / (r * ((float) M_PI))) + fmaf(r, (0.006944444444444444f / (s * (s * ((float) M_PI)))), (-0.041666666666666664f / (s * ((float) M_PI))))) / s);
}
function code(s, r)
	return Float32(Float32(Float32(exp(Float32(r / Float32(-s))) * Float32(0.25)) / Float32(r * Float32(s * Float32(Float32(pi) * Float32(2.0))))) + Float32(Float32(Float32(Float32(0.125) / Float32(r * Float32(pi))) + fma(r, Float32(Float32(0.006944444444444444) / Float32(s * Float32(s * Float32(pi)))), Float32(Float32(-0.041666666666666664) / Float32(s * Float32(pi))))) / s))
end
\begin{array}{l}

\\
\frac{e^{\frac{r}{-s}} \cdot 0.25}{r \cdot \left(s \cdot \left(\pi \cdot 2\right)\right)} + \frac{\frac{0.125}{r \cdot \pi} + \mathsf{fma}\left(r, \frac{0.006944444444444444}{s \cdot \left(s \cdot \pi\right)}, \frac{-0.041666666666666664}{s \cdot \pi}\right)}{s}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Add Preprocessing
  3. Taylor expanded in s around inf

    \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\left(\frac{1}{144} \cdot \frac{r}{{s}^{2} \cdot \mathsf{PI}\left(\right)} + \frac{1}{8} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}\right) - \frac{\frac{1}{24}}{s \cdot \mathsf{PI}\left(\right)}}{s}} \]
  4. Applied rewrites11.5%

    \[\leadsto \frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{0.125}{r \cdot \pi} + \mathsf{fma}\left(r, \frac{0.006944444444444444}{s \cdot \left(s \cdot \pi\right)}, \frac{-0.041666666666666664}{s \cdot \pi}\right)}{s}} \]
  5. Final simplification11.5%

    \[\leadsto \frac{e^{\frac{r}{-s}} \cdot 0.25}{r \cdot \left(s \cdot \left(\pi \cdot 2\right)\right)} + \frac{\frac{0.125}{r \cdot \pi} + \mathsf{fma}\left(r, \frac{0.006944444444444444}{s \cdot \left(s \cdot \pi\right)}, \frac{-0.041666666666666664}{s \cdot \pi}\right)}{s} \]
  6. Add Preprocessing

Alternative 6: 10.7% accurate, 1.4× speedup?

\[\begin{array}{l} \\ \frac{0.125 \cdot e^{\frac{r}{-s}}}{r \cdot \left(s \cdot \pi\right)} + \frac{\frac{0.125}{r \cdot \pi} + \mathsf{fma}\left(\frac{r}{s \cdot \left(s \cdot \pi\right)}, 0.006944444444444444, \frac{-0.041666666666666664}{s \cdot \pi}\right)}{s} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* 0.125 (exp (/ r (- s)))) (* r (* s PI)))
  (/
   (+
    (/ 0.125 (* r PI))
    (fma
     (/ r (* s (* s PI)))
     0.006944444444444444
     (/ -0.041666666666666664 (* s PI))))
   s)))
float code(float s, float r) {
	return ((0.125f * expf((r / -s))) / (r * (s * ((float) M_PI)))) + (((0.125f / (r * ((float) M_PI))) + fmaf((r / (s * (s * ((float) M_PI)))), 0.006944444444444444f, (-0.041666666666666664f / (s * ((float) M_PI))))) / s);
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.125) * exp(Float32(r / Float32(-s)))) / Float32(r * Float32(s * Float32(pi)))) + Float32(Float32(Float32(Float32(0.125) / Float32(r * Float32(pi))) + fma(Float32(r / Float32(s * Float32(s * Float32(pi)))), Float32(0.006944444444444444), Float32(Float32(-0.041666666666666664) / Float32(s * Float32(pi))))) / s))
end
\begin{array}{l}

\\
\frac{0.125 \cdot e^{\frac{r}{-s}}}{r \cdot \left(s \cdot \pi\right)} + \frac{\frac{0.125}{r \cdot \pi} + \mathsf{fma}\left(\frac{r}{s \cdot \left(s \cdot \pi\right)}, 0.006944444444444444, \frac{-0.041666666666666664}{s \cdot \pi}\right)}{s}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{3}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{\left(\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r}} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\color{blue}{\frac{3}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}}{\left(\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{\color{blue}{\left(\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r}} \]
    4. times-fracN/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{3}{4}}{\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}} \]
    5. associate-*l/N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s}} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\color{blue}{\left(6 \cdot \mathsf{PI}\left(\right)\right) \cdot s}} \]
    7. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\color{blue}{\left(6 \cdot \mathsf{PI}\left(\right)\right)} \cdot s} \]
    8. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot 6\right)} \cdot s} \]
    9. associate-*l*N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\color{blue}{\mathsf{PI}\left(\right) \cdot \left(6 \cdot s\right)}} \]
    10. associate-/r*N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s}} \]
    11. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{3 \cdot s}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s}} \]
  4. Applied rewrites99.5%

    \[\leadsto \frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \color{blue}{\frac{\frac{0.75 \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\pi}}{6 \cdot s}} \]
  5. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r}} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\color{blue}{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{\left(\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s\right) \cdot r}} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    4. times-fracN/A

      \[\leadsto \color{blue}{\frac{\frac{1}{4}}{\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r}} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    5. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{\left(2 \cdot \mathsf{PI}\left(\right)\right) \cdot s}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{\left(2 \cdot \mathsf{PI}\left(\right)\right)} \cdot s} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    7. associate-*l*N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{2 \cdot \left(\mathsf{PI}\left(\right) \cdot s\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    8. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{2 \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    9. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{2 \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    10. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{4}}{2}}{s \cdot \mathsf{PI}\left(\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    11. metadata-evalN/A

      \[\leadsto \frac{\color{blue}{\frac{1}{8}}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    12. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{\color{blue}{\mathsf{neg}\left(r\right)}}{s}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    13. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{\mathsf{neg}\left(r\right)}{s}}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    14. distribute-frac-negN/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\mathsf{neg}\left(\frac{r}{s}\right)}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    15. distribute-frac-neg2N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    16. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\color{blue}{\mathsf{neg}\left(s\right)}}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
    17. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}}}{r} + \frac{\frac{\frac{3}{4} \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\mathsf{PI}\left(\right)}}{6 \cdot s} \]
  6. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{0.125 \cdot e^{\frac{r}{-s}}}{r \cdot \left(s \cdot \pi\right)}} + \frac{\frac{0.75 \cdot \frac{e^{\frac{r}{s \cdot -3}}}{r}}{\pi}}{6 \cdot s} \]
  7. Taylor expanded in s around inf

    \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{r}{\mathsf{neg}\left(s\right)}}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)} + \color{blue}{\frac{\left(\frac{1}{144} \cdot \frac{r}{{s}^{2} \cdot \mathsf{PI}\left(\right)} + \frac{1}{8} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}\right) - \frac{\frac{1}{24}}{s \cdot \mathsf{PI}\left(\right)}}{s}} \]
  8. Applied rewrites11.5%

    \[\leadsto \frac{0.125 \cdot e^{\frac{r}{-s}}}{r \cdot \left(s \cdot \pi\right)} + \color{blue}{\frac{\frac{0.125}{r \cdot \pi} + \mathsf{fma}\left(\frac{r}{s \cdot \left(s \cdot \pi\right)}, 0.006944444444444444, \frac{-0.041666666666666664}{s \cdot \pi}\right)}{s}} \]
  9. Add Preprocessing

Alternative 7: 10.7% accurate, 1.6× speedup?

\[\begin{array}{l} \\ \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + \left(1 + \frac{\mathsf{fma}\left(r, -0.3333333333333333, 0.05555555555555555 \cdot \frac{r \cdot r}{s}\right)}{s}\right)}{r} \end{array} \]
(FPCore (s r)
 :precision binary32
 (*
  (/ 0.125 (* s PI))
  (/
   (+
    (exp (/ r (- s)))
    (+
     1.0
     (/ (fma r -0.3333333333333333 (* 0.05555555555555555 (/ (* r r) s))) s)))
   r)))
float code(float s, float r) {
	return (0.125f / (s * ((float) M_PI))) * ((expf((r / -s)) + (1.0f + (fmaf(r, -0.3333333333333333f, (0.05555555555555555f * ((r * r) / s))) / s))) / r);
}
function code(s, r)
	return Float32(Float32(Float32(0.125) / Float32(s * Float32(pi))) * Float32(Float32(exp(Float32(r / Float32(-s))) + Float32(Float32(1.0) + Float32(fma(r, Float32(-0.3333333333333333), Float32(Float32(0.05555555555555555) * Float32(Float32(r * r) / s))) / s))) / r))
end
\begin{array}{l}

\\
\frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + \left(1 + \frac{\mathsf{fma}\left(r, -0.3333333333333333, 0.05555555555555555 \cdot \frac{r \cdot r}{s}\right)}{s}\right)}{r}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Add Preprocessing
  3. Applied rewrites99.1%

    \[\leadsto \color{blue}{\frac{0.125}{s \cdot \pi} \cdot \left(\frac{e^{\frac{r}{s \cdot -3}}}{r} + \frac{e^{\frac{r}{-s}}}{r}\right)} \]
  4. Taylor expanded in r around inf

    \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r}} \]
  5. Step-by-step derivation
    1. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r}} \]
    2. lower-+.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{\color{blue}{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}}{r} \]
    3. lower-exp.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{\color{blue}{e^{-1 \cdot \frac{r}{s}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    4. mul-1-negN/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\mathsf{neg}\left(\frac{r}{s}\right)}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    5. distribute-neg-frac2N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    6. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    7. lower-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\color{blue}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
    8. lower-exp.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + \color{blue}{e^{\frac{-1}{3} \cdot \frac{r}{s}}}}{r} \]
    9. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\color{blue}{\frac{r}{s} \cdot \frac{-1}{3}}}}{r} \]
    10. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\color{blue}{\frac{r}{s} \cdot \frac{-1}{3}}}}{r} \]
    11. lower-/.f3299.0

      \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + e^{\color{blue}{\frac{r}{s}} \cdot -0.3333333333333333}}{r} \]
  6. Applied rewrites99.0%

    \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \color{blue}{\frac{e^{\frac{r}{-s}} + e^{\frac{r}{s} \cdot -0.3333333333333333}}{r}} \]
  7. Step-by-step derivation
    1. Applied rewrites99.1%

      \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + e^{\frac{r}{s \cdot -3}}}{r} \]
    2. Taylor expanded in s around -inf

      \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + \left(1 + -1 \cdot \frac{\frac{-1}{18} \cdot \frac{{r}^{2}}{s} + \frac{1}{3} \cdot r}{s}\right)}{r} \]
    3. Step-by-step derivation
      1. Applied rewrites11.5%

        \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + \left(1 + \frac{\mathsf{fma}\left(r, -0.3333333333333333, 0.05555555555555555 \cdot \frac{r \cdot r}{s}\right)}{s}\right)}{r} \]
      2. Add Preprocessing

      Alternative 8: 10.7% accurate, 1.6× speedup?

      \[\begin{array}{l} \\ \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + \mathsf{fma}\left(r, \mathsf{fma}\left(r, \frac{0.05555555555555555}{s \cdot s}, \frac{-0.3333333333333333}{s}\right), 1\right)}{r} \end{array} \]
      (FPCore (s r)
       :precision binary32
       (*
        (/ 0.125 (* s PI))
        (/
         (+
          (exp (/ r (- s)))
          (fma
           r
           (fma r (/ 0.05555555555555555 (* s s)) (/ -0.3333333333333333 s))
           1.0))
         r)))
      float code(float s, float r) {
      	return (0.125f / (s * ((float) M_PI))) * ((expf((r / -s)) + fmaf(r, fmaf(r, (0.05555555555555555f / (s * s)), (-0.3333333333333333f / s)), 1.0f)) / r);
      }
      
      function code(s, r)
      	return Float32(Float32(Float32(0.125) / Float32(s * Float32(pi))) * Float32(Float32(exp(Float32(r / Float32(-s))) + fma(r, fma(r, Float32(Float32(0.05555555555555555) / Float32(s * s)), Float32(Float32(-0.3333333333333333) / s)), Float32(1.0))) / r))
      end
      
      \begin{array}{l}
      
      \\
      \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + \mathsf{fma}\left(r, \mathsf{fma}\left(r, \frac{0.05555555555555555}{s \cdot s}, \frac{-0.3333333333333333}{s}\right), 1\right)}{r}
      \end{array}
      
      Derivation
      1. Initial program 99.5%

        \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
      2. Add Preprocessing
      3. Applied rewrites99.1%

        \[\leadsto \color{blue}{\frac{0.125}{s \cdot \pi} \cdot \left(\frac{e^{\frac{r}{s \cdot -3}}}{r} + \frac{e^{\frac{r}{-s}}}{r}\right)} \]
      4. Taylor expanded in r around inf

        \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r}} \]
      5. Step-by-step derivation
        1. lower-/.f32N/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r}} \]
        2. lower-+.f32N/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{\color{blue}{e^{-1 \cdot \frac{r}{s}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}}{r} \]
        3. lower-exp.f32N/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{\color{blue}{e^{-1 \cdot \frac{r}{s}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
        4. mul-1-negN/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\mathsf{neg}\left(\frac{r}{s}\right)}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
        5. distribute-neg-frac2N/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
        6. lower-/.f32N/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\color{blue}{\frac{r}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
        7. lower-neg.f32N/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\color{blue}{\mathsf{neg}\left(s\right)}}} + e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r} \]
        8. lower-exp.f32N/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + \color{blue}{e^{\frac{-1}{3} \cdot \frac{r}{s}}}}{r} \]
        9. *-commutativeN/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\color{blue}{\frac{r}{s} \cdot \frac{-1}{3}}}}{r} \]
        10. lower-*.f32N/A

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + e^{\color{blue}{\frac{r}{s} \cdot \frac{-1}{3}}}}{r} \]
        11. lower-/.f3299.0

          \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + e^{\color{blue}{\frac{r}{s}} \cdot -0.3333333333333333}}{r} \]
      6. Applied rewrites99.0%

        \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \color{blue}{\frac{e^{\frac{r}{-s}} + e^{\frac{r}{s} \cdot -0.3333333333333333}}{r}} \]
      7. Step-by-step derivation
        1. Applied rewrites99.1%

          \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + e^{\frac{r}{s \cdot -3}}}{r} \]
        2. Taylor expanded in r around 0

          \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{r}{\mathsf{neg}\left(s\right)}} + \left(1 + r \cdot \left(\frac{1}{18} \cdot \frac{r}{{s}^{2}} - \frac{1}{3} \cdot \frac{1}{s}\right)\right)}{r} \]
        3. Step-by-step derivation
          1. Applied rewrites11.5%

            \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \frac{e^{\frac{r}{-s}} + \mathsf{fma}\left(r, \mathsf{fma}\left(r, \frac{0.05555555555555555}{s \cdot s}, \frac{-0.3333333333333333}{s}\right), 1\right)}{r} \]
          2. Add Preprocessing

          Alternative 9: 10.1% accurate, 4.5× speedup?

          \[\begin{array}{l} \\ \frac{0.125 \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(-r, \frac{0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right)}{s \cdot \pi} \end{array} \]
          (FPCore (s r)
           :precision binary32
           (/
            (*
             0.125
             (- (/ 2.0 r) (/ (fma (- r) (/ 0.5555555555555556 s) 1.3333333333333333) s)))
            (* s PI)))
          float code(float s, float r) {
          	return (0.125f * ((2.0f / r) - (fmaf(-r, (0.5555555555555556f / s), 1.3333333333333333f) / s))) / (s * ((float) M_PI));
          }
          
          function code(s, r)
          	return Float32(Float32(Float32(0.125) * Float32(Float32(Float32(2.0) / r) - Float32(fma(Float32(-r), Float32(Float32(0.5555555555555556) / s), Float32(1.3333333333333333)) / s))) / Float32(s * Float32(pi)))
          end
          
          \begin{array}{l}
          
          \\
          \frac{0.125 \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(-r, \frac{0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right)}{s \cdot \pi}
          \end{array}
          
          Derivation
          1. Initial program 99.5%

            \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
          2. Add Preprocessing
          3. Applied rewrites99.1%

            \[\leadsto \color{blue}{\frac{0.125}{s \cdot \pi} \cdot \left(\frac{e^{\frac{r}{s \cdot -3}}}{r} + \frac{e^{\frac{r}{-s}}}{r}\right)} \]
          4. Taylor expanded in s around inf

            \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\left(\left(\frac{1}{18} \cdot \frac{r}{{s}^{2}} + \left(\frac{1}{2} \cdot \frac{r}{{s}^{2}} + 2 \cdot \frac{1}{r}\right)\right) - \frac{4}{3} \cdot \frac{1}{s}\right)} \]
          5. Applied rewrites11.1%

            \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \color{blue}{\left(\frac{2}{r} - \frac{\mathsf{fma}\left(-r, \frac{0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right)} \]
          6. Step-by-step derivation
            1. lift-*.f32N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(\mathsf{neg}\left(r\right), \frac{\frac{5}{9}}{s}, \frac{4}{3}\right)}{s}\right)} \]
            2. lift-/.f32N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)}} \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(\mathsf{neg}\left(r\right), \frac{\frac{5}{9}}{s}, \frac{4}{3}\right)}{s}\right) \]
            3. associate-*l/N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{8} \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(\mathsf{neg}\left(r\right), \frac{\frac{5}{9}}{s}, \frac{4}{3}\right)}{s}\right)}{s \cdot \mathsf{PI}\left(\right)}} \]
            4. lower-/.f32N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{8} \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(\mathsf{neg}\left(r\right), \frac{\frac{5}{9}}{s}, \frac{4}{3}\right)}{s}\right)}{s \cdot \mathsf{PI}\left(\right)}} \]
            5. lower-*.f3211.1

              \[\leadsto \frac{\color{blue}{0.125 \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(-r, \frac{0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right)}}{s \cdot \pi} \]
          7. Applied rewrites11.1%

            \[\leadsto \color{blue}{\frac{0.125 \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(-r, \frac{0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right)}{s \cdot \pi}} \]
          8. Add Preprocessing

          Alternative 10: 10.1% accurate, 4.6× speedup?

          \[\begin{array}{l} \\ \frac{0.125}{s \cdot \pi} \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(r, \frac{-0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right) \end{array} \]
          (FPCore (s r)
           :precision binary32
           (*
            (/ 0.125 (* s PI))
            (- (/ 2.0 r) (/ (fma r (/ -0.5555555555555556 s) 1.3333333333333333) s))))
          float code(float s, float r) {
          	return (0.125f / (s * ((float) M_PI))) * ((2.0f / r) - (fmaf(r, (-0.5555555555555556f / s), 1.3333333333333333f) / s));
          }
          
          function code(s, r)
          	return Float32(Float32(Float32(0.125) / Float32(s * Float32(pi))) * Float32(Float32(Float32(2.0) / r) - Float32(fma(r, Float32(Float32(-0.5555555555555556) / s), Float32(1.3333333333333333)) / s)))
          end
          
          \begin{array}{l}
          
          \\
          \frac{0.125}{s \cdot \pi} \cdot \left(\frac{2}{r} - \frac{\mathsf{fma}\left(r, \frac{-0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right)
          \end{array}
          
          Derivation
          1. Initial program 99.5%

            \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
          2. Add Preprocessing
          3. Applied rewrites99.1%

            \[\leadsto \color{blue}{\frac{0.125}{s \cdot \pi} \cdot \left(\frac{e^{\frac{r}{s \cdot -3}}}{r} + \frac{e^{\frac{r}{-s}}}{r}\right)} \]
          4. Taylor expanded in s around inf

            \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\left(\left(\frac{1}{18} \cdot \frac{r}{{s}^{2}} + \left(\frac{1}{2} \cdot \frac{r}{{s}^{2}} + 2 \cdot \frac{1}{r}\right)\right) - \frac{4}{3} \cdot \frac{1}{s}\right)} \]
          5. Applied rewrites11.1%

            \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \color{blue}{\left(\frac{2}{r} - \frac{\mathsf{fma}\left(-r, \frac{0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right)} \]
          6. Taylor expanded in s around inf

            \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\left(\left(\frac{1}{18} \cdot \frac{r}{{s}^{2}} + \left(\frac{1}{2} \cdot \frac{r}{{s}^{2}} + 2 \cdot \frac{1}{r}\right)\right) - \frac{4}{3} \cdot \frac{1}{s}\right)} \]
          7. Applied rewrites11.1%

            \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \color{blue}{\left(\frac{2}{r} - \frac{\mathsf{fma}\left(r, \frac{-0.5555555555555556}{s}, 1.3333333333333333\right)}{s}\right)} \]
          8. Add Preprocessing

          Alternative 11: 9.1% accurate, 6.3× speedup?

          \[\begin{array}{l} \\ \frac{0.125}{s \cdot \pi} \cdot \left(\frac{2}{r} + \frac{-1.3333333333333333}{s}\right) \end{array} \]
          (FPCore (s r)
           :precision binary32
           (* (/ 0.125 (* s PI)) (+ (/ 2.0 r) (/ -1.3333333333333333 s))))
          float code(float s, float r) {
          	return (0.125f / (s * ((float) M_PI))) * ((2.0f / r) + (-1.3333333333333333f / s));
          }
          
          function code(s, r)
          	return Float32(Float32(Float32(0.125) / Float32(s * Float32(pi))) * Float32(Float32(Float32(2.0) / r) + Float32(Float32(-1.3333333333333333) / s)))
          end
          
          function tmp = code(s, r)
          	tmp = (single(0.125) / (s * single(pi))) * ((single(2.0) / r) + (single(-1.3333333333333333) / s));
          end
          
          \begin{array}{l}
          
          \\
          \frac{0.125}{s \cdot \pi} \cdot \left(\frac{2}{r} + \frac{-1.3333333333333333}{s}\right)
          \end{array}
          
          Derivation
          1. Initial program 99.5%

            \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
          2. Add Preprocessing
          3. Applied rewrites99.1%

            \[\leadsto \color{blue}{\frac{0.125}{s \cdot \pi} \cdot \left(\frac{e^{\frac{r}{s \cdot -3}}}{r} + \frac{e^{\frac{r}{-s}}}{r}\right)} \]
          4. Taylor expanded in s around inf

            \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\left(2 \cdot \frac{1}{r} - \frac{4}{3} \cdot \frac{1}{s}\right)} \]
          5. Step-by-step derivation
            1. sub-negN/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\left(2 \cdot \frac{1}{r} + \left(\mathsf{neg}\left(\frac{4}{3} \cdot \frac{1}{s}\right)\right)\right)} \]
            2. lower-+.f32N/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \color{blue}{\left(2 \cdot \frac{1}{r} + \left(\mathsf{neg}\left(\frac{4}{3} \cdot \frac{1}{s}\right)\right)\right)} \]
            3. associate-*r/N/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \left(\color{blue}{\frac{2 \cdot 1}{r}} + \left(\mathsf{neg}\left(\frac{4}{3} \cdot \frac{1}{s}\right)\right)\right) \]
            4. metadata-evalN/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \left(\frac{\color{blue}{2}}{r} + \left(\mathsf{neg}\left(\frac{4}{3} \cdot \frac{1}{s}\right)\right)\right) \]
            5. lower-/.f32N/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \left(\color{blue}{\frac{2}{r}} + \left(\mathsf{neg}\left(\frac{4}{3} \cdot \frac{1}{s}\right)\right)\right) \]
            6. associate-*r/N/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \left(\frac{2}{r} + \left(\mathsf{neg}\left(\color{blue}{\frac{\frac{4}{3} \cdot 1}{s}}\right)\right)\right) \]
            7. metadata-evalN/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \left(\frac{2}{r} + \left(\mathsf{neg}\left(\frac{\color{blue}{\frac{4}{3}}}{s}\right)\right)\right) \]
            8. distribute-neg-fracN/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \left(\frac{2}{r} + \color{blue}{\frac{\mathsf{neg}\left(\frac{4}{3}\right)}{s}}\right) \]
            9. metadata-evalN/A

              \[\leadsto \frac{\frac{1}{8}}{s \cdot \mathsf{PI}\left(\right)} \cdot \left(\frac{2}{r} + \frac{\color{blue}{\frac{-4}{3}}}{s}\right) \]
            10. lower-/.f3210.2

              \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \left(\frac{2}{r} + \color{blue}{\frac{-1.3333333333333333}{s}}\right) \]
          6. Applied rewrites10.2%

            \[\leadsto \frac{0.125}{s \cdot \pi} \cdot \color{blue}{\left(\frac{2}{r} + \frac{-1.3333333333333333}{s}\right)} \]
          7. Add Preprocessing

          Alternative 12: 9.1% accurate, 6.5× speedup?

          \[\begin{array}{l} \\ \frac{0.25}{r \cdot \left(s \cdot \pi\right)} + \frac{-0.16666666666666666}{s \cdot \left(s \cdot \pi\right)} \end{array} \]
          (FPCore (s r)
           :precision binary32
           (+ (/ 0.25 (* r (* s PI))) (/ -0.16666666666666666 (* s (* s PI)))))
          float code(float s, float r) {
          	return (0.25f / (r * (s * ((float) M_PI)))) + (-0.16666666666666666f / (s * (s * ((float) M_PI))));
          }
          
          function code(s, r)
          	return Float32(Float32(Float32(0.25) / Float32(r * Float32(s * Float32(pi)))) + Float32(Float32(-0.16666666666666666) / Float32(s * Float32(s * Float32(pi)))))
          end
          
          function tmp = code(s, r)
          	tmp = (single(0.25) / (r * (s * single(pi)))) + (single(-0.16666666666666666) / (s * (s * single(pi))));
          end
          
          \begin{array}{l}
          
          \\
          \frac{0.25}{r \cdot \left(s \cdot \pi\right)} + \frac{-0.16666666666666666}{s \cdot \left(s \cdot \pi\right)}
          \end{array}
          
          Derivation
          1. Initial program 99.5%

            \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
          2. Add Preprocessing
          3. Taylor expanded in s around inf

            \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)} - \frac{1}{6} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s}} \]
          4. Step-by-step derivation
            1. div-subN/A

              \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}}{s} - \frac{\frac{1}{6} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s}} \]
            2. sub-negN/A

              \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}}{s} + \left(\mathsf{neg}\left(\frac{\frac{1}{6} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s}\right)\right)} \]
            3. associate-/l*N/A

              \[\leadsto \frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}}{s} + \left(\mathsf{neg}\left(\color{blue}{\frac{1}{6} \cdot \frac{\frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s}}\right)\right) \]
            4. associate-/l/N/A

              \[\leadsto \frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}}{s} + \left(\mathsf{neg}\left(\frac{1}{6} \cdot \color{blue}{\frac{1}{s \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}}\right)\right) \]
            5. associate-*l*N/A

              \[\leadsto \frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}}{s} + \left(\mathsf{neg}\left(\frac{1}{6} \cdot \frac{1}{\color{blue}{\left(s \cdot s\right) \cdot \mathsf{PI}\left(\right)}}\right)\right) \]
            6. unpow2N/A

              \[\leadsto \frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}}{s} + \left(\mathsf{neg}\left(\frac{1}{6} \cdot \frac{1}{\color{blue}{{s}^{2}} \cdot \mathsf{PI}\left(\right)}\right)\right) \]
            7. lower-+.f32N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}}{s} + \left(\mathsf{neg}\left(\frac{1}{6} \cdot \frac{1}{{s}^{2} \cdot \mathsf{PI}\left(\right)}\right)\right)} \]
          5. Applied rewrites10.1%

            \[\leadsto \color{blue}{\frac{0.25}{r \cdot \left(s \cdot \pi\right)} + \frac{-0.16666666666666666}{s \cdot \left(s \cdot \pi\right)}} \]
          6. Add Preprocessing

          Alternative 13: 9.1% accurate, 10.6× speedup?

          \[\begin{array}{l} \\ \frac{\frac{0.25}{\pi}}{r \cdot s} \end{array} \]
          (FPCore (s r) :precision binary32 (/ (/ 0.25 PI) (* r s)))
          float code(float s, float r) {
          	return (0.25f / ((float) M_PI)) / (r * s);
          }
          
          function code(s, r)
          	return Float32(Float32(Float32(0.25) / Float32(pi)) / Float32(r * s))
          end
          
          function tmp = code(s, r)
          	tmp = (single(0.25) / single(pi)) / (r * s);
          end
          
          \begin{array}{l}
          
          \\
          \frac{\frac{0.25}{\pi}}{r \cdot s}
          \end{array}
          
          Derivation
          1. Initial program 99.5%

            \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
          2. Add Preprocessing
          3. Taylor expanded in r around 0

            \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
          4. Step-by-step derivation
            1. lower-/.f32N/A

              \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
            2. lower-*.f32N/A

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

              \[\leadsto \frac{\frac{1}{4}}{r \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
            4. lower-PI.f3210.0

              \[\leadsto \frac{0.25}{r \cdot \left(s \cdot \color{blue}{\pi}\right)} \]
          5. Applied rewrites10.0%

            \[\leadsto \color{blue}{\frac{0.25}{r \cdot \left(s \cdot \pi\right)}} \]
          6. Step-by-step derivation
            1. Applied rewrites10.1%

              \[\leadsto \frac{\frac{0.25}{\pi}}{\color{blue}{r \cdot s}} \]
            2. Add Preprocessing

            Alternative 14: 9.1% accurate, 13.5× speedup?

            \[\begin{array}{l} \\ \frac{0.25}{\pi \cdot \left(r \cdot s\right)} \end{array} \]
            (FPCore (s r) :precision binary32 (/ 0.25 (* PI (* r s))))
            float code(float s, float r) {
            	return 0.25f / (((float) M_PI) * (r * s));
            }
            
            function code(s, r)
            	return Float32(Float32(0.25) / Float32(Float32(pi) * Float32(r * s)))
            end
            
            function tmp = code(s, r)
            	tmp = single(0.25) / (single(pi) * (r * s));
            end
            
            \begin{array}{l}
            
            \\
            \frac{0.25}{\pi \cdot \left(r \cdot s\right)}
            \end{array}
            
            Derivation
            1. Initial program 99.5%

              \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
            2. Add Preprocessing
            3. Taylor expanded in r around 0

              \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
            4. Step-by-step derivation
              1. lower-/.f32N/A

                \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
              2. lower-*.f32N/A

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

                \[\leadsto \frac{\frac{1}{4}}{r \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
              4. lower-PI.f3210.0

                \[\leadsto \frac{0.25}{r \cdot \left(s \cdot \color{blue}{\pi}\right)} \]
            5. Applied rewrites10.0%

              \[\leadsto \color{blue}{\frac{0.25}{r \cdot \left(s \cdot \pi\right)}} \]
            6. Step-by-step derivation
              1. Applied rewrites10.1%

                \[\leadsto \frac{0.25}{\left(r \cdot s\right) \cdot \color{blue}{\pi}} \]
              2. Final simplification10.1%

                \[\leadsto \frac{0.25}{\pi \cdot \left(r \cdot s\right)} \]
              3. Add Preprocessing

              Alternative 15: 9.1% accurate, 13.5× speedup?

              \[\begin{array}{l} \\ \frac{0.25}{r \cdot \left(s \cdot \pi\right)} \end{array} \]
              (FPCore (s r) :precision binary32 (/ 0.25 (* r (* s PI))))
              float code(float s, float r) {
              	return 0.25f / (r * (s * ((float) M_PI)));
              }
              
              function code(s, r)
              	return Float32(Float32(0.25) / Float32(r * Float32(s * Float32(pi))))
              end
              
              function tmp = code(s, r)
              	tmp = single(0.25) / (r * (s * single(pi)));
              end
              
              \begin{array}{l}
              
              \\
              \frac{0.25}{r \cdot \left(s \cdot \pi\right)}
              \end{array}
              
              Derivation
              1. Initial program 99.5%

                \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
              2. Add Preprocessing
              3. Taylor expanded in r around 0

                \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
              4. Step-by-step derivation
                1. lower-/.f32N/A

                  \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
                2. lower-*.f32N/A

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

                  \[\leadsto \frac{\frac{1}{4}}{r \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
                4. lower-PI.f3210.0

                  \[\leadsto \frac{0.25}{r \cdot \left(s \cdot \color{blue}{\pi}\right)} \]
              5. Applied rewrites10.0%

                \[\leadsto \color{blue}{\frac{0.25}{r \cdot \left(s \cdot \pi\right)}} \]
              6. Add Preprocessing

              Reproduce

              ?
              herbie shell --seed 2024234 
              (FPCore (s r)
                :name "Disney BSSRDF, PDF of scattering profile"
                :precision binary32
                :pre (and (and (<= 0.0 s) (<= s 256.0)) (and (< 1e-6 r) (< r 1000000.0)))
                (+ (/ (* 0.25 (exp (/ (- r) s))) (* (* (* 2.0 PI) s) r)) (/ (* 0.75 (exp (/ (- r) (* 3.0 s)))) (* (* (* 6.0 PI) s) r))))