Disney BSSRDF, sample scattering profile, upper

Percentage Accurate: 95.9% → 98.3%

Time: 10.5s

Alternatives: 9

Speedup: 1.2×

Specification

\[\left(0 \leq s \land s \leq 256\right) \land \left(0.25 \leq u \land u \leq 1\right)\]

Math

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

FPCore

(FPCore (s u)
 :precision binary32
 (* (* 3.0 s) (log (/ 1.0 (- 1.0 (/ (- u 0.25) 0.75))))))

C

float code(float s, float u) {
	return (3.0f * s) * logf((1.0f / (1.0f - ((u - 0.25f) / 0.75f))));
}

Fortran

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

Julia

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

MATLAB

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

Initial Program: 95.9% accurate, 1.0× speedup

Math

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

FPCore

(FPCore (s u)
 :precision binary32
 (* (* 3.0 s) (log (/ 1.0 (- 1.0 (/ (- u 0.25) 0.75))))))

C

float code(float s, float u) {
	return (3.0f * s) * logf((1.0f / (1.0f - ((u - 0.25f) / 0.75f))));
}

Fortran

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

Julia

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

MATLAB

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

Alternative 1: 98.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \left(s \cdot \left(\mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(1.7777777777777777, u, 0.8888888888888888\right)\right) - \mathsf{log1p}\left(\left(u + -0.25\right) \cdot \left(\left(u + -0.25\right) \cdot \left(\left(u + -0.25\right) \cdot -2.3703703703703702\right)\right)\right)\right)\right) \cdot 3 \end{array} \]

FPCore

(FPCore (s u)
 :precision binary32
 (*
  (*
   s
   (-
    (log1p (* (+ u -0.25) (fma 1.7777777777777777 u 0.8888888888888888)))
    (log1p
     (* (+ u -0.25) (* (+ u -0.25) (* (+ u -0.25) -2.3703703703703702))))))
  3.0))

C

float code(float s, float u) {
	return (s * (log1pf(((u + -0.25f) * fmaf(1.7777777777777777f, u, 0.8888888888888888f))) - log1pf(((u + -0.25f) * ((u + -0.25f) * ((u + -0.25f) * -2.3703703703703702f)))))) * 3.0f;
}

Julia

function code(s, u)
	return Float32(Float32(s * Float32(log1p(Float32(Float32(u + Float32(-0.25)) * fma(Float32(1.7777777777777777), u, Float32(0.8888888888888888)))) - log1p(Float32(Float32(u + Float32(-0.25)) * Float32(Float32(u + Float32(-0.25)) * Float32(Float32(u + Float32(-0.25)) * Float32(-2.3703703703703702))))))) * Float32(3.0))
end

Derivation

1. Initial program 96.0%

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

   1. lift-*.f32 N/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-*.f32 N/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. *-commutative N/A

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

   5. lower-*.f32 N/A

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

4. Applied rewrites 98.0%

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

   1. lift-log1p.f32 N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \color{blue}{\log \left(1 + \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)}\right) \cdot 3 \]

   2. flip3-+ N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \log \color{blue}{\left(\frac{{1}^{3} + {\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}^{3}}{1 \cdot 1 + \left(\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) - 1 \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)}\right)}\right) \cdot 3 \]

   3. log-div N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \color{blue}{\left(\log \left({1}^{3} + {\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}^{3}\right) - \log \left(1 \cdot 1 + \left(\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) - 1 \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)\right)\right)}\right) \cdot 3 \]

   4. metadata-eval N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\log \left({1}^{3} + {\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}^{3}\right) - \log \left(\color{blue}{1} + \left(\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) - 1 \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)\right)\right)\right) \cdot 3 \]

   5. sub-neg N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\log \left({1}^{3} + {\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}^{3}\right) - \log \left(1 + \color{blue}{\left(\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) + \left(\mathsf{neg}\left(1 \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)\right)\right)}\right)\right)\right) \cdot 3 \]

6. Applied rewrites 98.4%

   \[\leadsto \left(\left(-s\right) \cdot \color{blue}{\left(\mathsf{log1p}\left(\left(u + -0.25\right) \cdot \left(\left(u + -0.25\right) \cdot \left(\left(u + -0.25\right) \cdot -2.3703703703703702\right)\right)\right) - \mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(1.7777777777777777, u, 0.8888888888888888\right)\right)\right)}\right) \cdot 3 \]

7. Final simplification 98.4%

   \[\leadsto \left(s \cdot \left(\mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(1.7777777777777777, u, 0.8888888888888888\right)\right) - \mathsf{log1p}\left(\left(u + -0.25\right) \cdot \left(\left(u + -0.25\right) \cdot \left(\left(u + -0.25\right) \cdot -2.3703703703703702\right)\right)\right)\right)\right) \cdot 3 \]
8. Add Preprocessing

Alternative 2: 98.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ 3 \cdot \left(s \cdot \left(\mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(1.7777777777777777, u, 0.8888888888888888\right)\right) - \mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(u, \mathsf{fma}\left(-2.3703703703703702, u, 1.1851851851851851\right), -0.14814814814814814\right)\right)\right)\right) \end{array} \]

FPCore

(FPCore (s u)
 :precision binary32
 (*
  3.0
  (*
   s
   (-
    (log1p (* (+ u -0.25) (fma 1.7777777777777777 u 0.8888888888888888)))
    (log1p
     (*
      (+ u -0.25)
      (fma
       u
       (fma -2.3703703703703702 u 1.1851851851851851)
       -0.14814814814814814)))))))

C

float code(float s, float u) {
	return 3.0f * (s * (log1pf(((u + -0.25f) * fmaf(1.7777777777777777f, u, 0.8888888888888888f))) - log1pf(((u + -0.25f) * fmaf(u, fmaf(-2.3703703703703702f, u, 1.1851851851851851f), -0.14814814814814814f)))));
}

Julia

function code(s, u)
	return Float32(Float32(3.0) * Float32(s * Float32(log1p(Float32(Float32(u + Float32(-0.25)) * fma(Float32(1.7777777777777777), u, Float32(0.8888888888888888)))) - log1p(Float32(Float32(u + Float32(-0.25)) * fma(u, fma(Float32(-2.3703703703703702), u, Float32(1.1851851851851851)), Float32(-0.14814814814814814)))))))
end

Derivation

1. Initial program 96.0%

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

   1. lift-*.f32 N/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-*.f32 N/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. *-commutative N/A

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

   5. lower-*.f32 N/A

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

4. Applied rewrites 98.0%

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

   1. lift-log1p.f32 N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \color{blue}{\log \left(1 + \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)}\right) \cdot 3 \]

   2. flip3-+ N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \log \color{blue}{\left(\frac{{1}^{3} + {\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}^{3}}{1 \cdot 1 + \left(\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) - 1 \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)}\right)}\right) \cdot 3 \]

   3. log-div N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \color{blue}{\left(\log \left({1}^{3} + {\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}^{3}\right) - \log \left(1 \cdot 1 + \left(\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) - 1 \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)\right)\right)}\right) \cdot 3 \]

   4. metadata-eval N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\log \left({1}^{3} + {\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}^{3}\right) - \log \left(\color{blue}{1} + \left(\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) - 1 \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)\right)\right)\right) \cdot 3 \]

   5. sub-neg N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\log \left({1}^{3} + {\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}^{3}\right) - \log \left(1 + \color{blue}{\left(\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right) + \left(\mathsf{neg}\left(1 \cdot \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)\right)\right)}\right)\right)\right) \cdot 3 \]

6. Applied rewrites 98.4%

   \[\leadsto \left(\left(-s\right) \cdot \color{blue}{\left(\mathsf{log1p}\left(\left(u + -0.25\right) \cdot \left(\left(u + -0.25\right) \cdot \left(\left(u + -0.25\right) \cdot -2.3703703703703702\right)\right)\right) - \mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(1.7777777777777777, u, 0.8888888888888888\right)\right)\right)}\right) \cdot 3 \]

7. Taylor expanded in u around 0

   \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \color{blue}{\left(u \cdot \left(\frac{32}{27} + \frac{-64}{27} \cdot u\right) - \frac{4}{27}\right)}\right) - \mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \mathsf{fma}\left(\frac{16}{9}, u, \frac{8}{9}\right)\right)\right)\right) \cdot 3 \]
8. Step-by-step derivation

   1. sub-neg N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \color{blue}{\left(u \cdot \left(\frac{32}{27} + \frac{-64}{27} \cdot u\right) + \left(\mathsf{neg}\left(\frac{4}{27}\right)\right)\right)}\right) - \mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \mathsf{fma}\left(\frac{16}{9}, u, \frac{8}{9}\right)\right)\right)\right) \cdot 3 \]

   2. lower-fma.f32 N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \color{blue}{\mathsf{fma}\left(u, \frac{32}{27} + \frac{-64}{27} \cdot u, \mathsf{neg}\left(\frac{4}{27}\right)\right)}\right) - \mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \mathsf{fma}\left(\frac{16}{9}, u, \frac{8}{9}\right)\right)\right)\right) \cdot 3 \]

   3. +-commutative N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \mathsf{fma}\left(u, \color{blue}{\frac{-64}{27} \cdot u + \frac{32}{27}}, \mathsf{neg}\left(\frac{4}{27}\right)\right)\right) - \mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \mathsf{fma}\left(\frac{16}{9}, u, \frac{8}{9}\right)\right)\right)\right) \cdot 3 \]

   4. lower-fma.f32 N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \left(\mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \mathsf{fma}\left(u, \color{blue}{\mathsf{fma}\left(\frac{-64}{27}, u, \frac{32}{27}\right)}, \mathsf{neg}\left(\frac{4}{27}\right)\right)\right) - \mathsf{log1p}\left(\left(u + \frac{-1}{4}\right) \cdot \mathsf{fma}\left(\frac{16}{9}, u, \frac{8}{9}\right)\right)\right)\right) \cdot 3 \]

   5. metadata-eval 98.4

      \[\leadsto \left(\left(-s\right) \cdot \left(\mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(u, \mathsf{fma}\left(-2.3703703703703702, u, 1.1851851851851851\right), \color{blue}{-0.14814814814814814}\right)\right) - \mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(1.7777777777777777, u, 0.8888888888888888\right)\right)\right)\right) \cdot 3 \]

9. Applied rewrites 98.4%

   \[\leadsto \left(\left(-s\right) \cdot \left(\mathsf{log1p}\left(\left(u + -0.25\right) \cdot \color{blue}{\mathsf{fma}\left(u, \mathsf{fma}\left(-2.3703703703703702, u, 1.1851851851851851\right), -0.14814814814814814\right)}\right) - \mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(1.7777777777777777, u, 0.8888888888888888\right)\right)\right)\right) \cdot 3 \]

10. Final simplification 98.4%

    \[\leadsto 3 \cdot \left(s \cdot \left(\mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(1.7777777777777777, u, 0.8888888888888888\right)\right) - \mathsf{log1p}\left(\left(u + -0.25\right) \cdot \mathsf{fma}\left(u, \mathsf{fma}\left(-2.3703703703703702, u, 1.1851851851851851\right), -0.14814814814814814\right)\right)\right)\right) \]
11. Add Preprocessing

Alternative 3: 98.2% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ 3 \cdot \left(s \cdot \mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right) - s \cdot \mathsf{log1p}\left(\mathsf{fma}\left(1.7777777777777777, u, -0.4444444444444444\right) \cdot \left(0.25 - u\right)\right)\right) \end{array} \]

FPCore

(FPCore (s u)
 :precision binary32
 (*
  3.0
  (-
   (* s (log1p (fma u 1.3333333333333333 -0.3333333333333333)))
   (*
    s
    (log1p (* (fma 1.7777777777777777 u -0.4444444444444444) (- 0.25 u)))))))

C

float code(float s, float u) {
	return 3.0f * ((s * log1pf(fmaf(u, 1.3333333333333333f, -0.3333333333333333f))) - (s * log1pf((fmaf(1.7777777777777777f, u, -0.4444444444444444f) * (0.25f - u)))));
}

Julia

function code(s, u)
	return Float32(Float32(3.0) * Float32(Float32(s * log1p(fma(u, Float32(1.3333333333333333), Float32(-0.3333333333333333)))) - Float32(s * log1p(Float32(fma(Float32(1.7777777777777777), u, Float32(-0.4444444444444444)) * Float32(Float32(0.25) - u))))))
end

Derivation

1. Initial program 96.0%

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

   1. lift-*.f32 N/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-*.f32 N/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. *-commutative N/A

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

   5. lower-*.f32 N/A

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

4. Applied rewrites 98.0%

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

   1. lift-*.f32 N/A

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

   2. lift-neg.f32 N/A

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

   3. distribute-lft-neg-out N/A

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

   4. distribute-rgt-neg-in N/A

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

   5. lift-log1p.f32 N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\color{blue}{\log \left(1 + \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)}\right)\right)\right) \cdot 3 \]

   6. lift-neg.f32 N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 + \color{blue}{\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}\right)\right)\right)\right) \cdot 3 \]

   7. unsub-neg N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \color{blue}{\left(1 - \mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)}\right)\right)\right) \cdot 3 \]

   8. lift-fma.f32 N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \color{blue}{\left(u \cdot \frac{4}{3} + \frac{-1}{3}\right)}\right)\right)\right)\right) \cdot 3 \]

   9. metadata-eval N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \left(u \cdot \frac{4}{3} + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{3}\right)\right)}\right)\right)\right)\right)\right) \cdot 3 \]

   10. metadata-eval N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \left(u \cdot \frac{4}{3} + \left(\mathsf{neg}\left(\color{blue}{\frac{\frac{1}{4}}{\frac{3}{4}}}\right)\right)\right)\right)\right)\right)\right) \cdot 3 \]

   11. sub-neg N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \color{blue}{\left(u \cdot \frac{4}{3} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)}\right)\right)\right)\right) \cdot 3 \]

   12. metadata-eval N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \left(u \cdot \color{blue}{\frac{1}{\frac{3}{4}}} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)\right)\right)\right) \cdot 3 \]

   13. div-inv N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \left(\color{blue}{\frac{u}{\frac{3}{4}}} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)\right)\right)\right) \cdot 3 \]

   14. div-sub N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \color{blue}{\frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)\right)\right)\right) \cdot 3 \]

   15. neg-log N/A

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

   16. flip-- N/A

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

   17. associate-/r/ N/A

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

6. Applied rewrites 98.4%

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

7. Final simplification 98.4%

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

Alternative 4: 98.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ 3 \cdot \mathsf{fma}\left(\mathsf{log1p}\left(\mathsf{fma}\left(u, 1.3333333333333333, -0.3333333333333333\right)\right), s, \left(-s\right) \cdot \mathsf{log1p}\left(\mathsf{fma}\left(1.7777777777777777, u, -0.4444444444444444\right) \cdot \left(0.25 - u\right)\right)\right) \end{array} \]

FPCore

(FPCore (s u)
 :precision binary32
 (*
  3.0
  (fma
   (log1p (fma u 1.3333333333333333 -0.3333333333333333))
   s
   (*
    (- s)
    (log1p (* (fma 1.7777777777777777 u -0.4444444444444444) (- 0.25 u)))))))

C

float code(float s, float u) {
	return 3.0f * fmaf(log1pf(fmaf(u, 1.3333333333333333f, -0.3333333333333333f)), s, (-s * log1pf((fmaf(1.7777777777777777f, u, -0.4444444444444444f) * (0.25f - u)))));
}

Julia

function code(s, u)
	return Float32(Float32(3.0) * fma(log1p(fma(u, Float32(1.3333333333333333), Float32(-0.3333333333333333))), s, Float32(Float32(-s) * log1p(Float32(fma(Float32(1.7777777777777777), u, Float32(-0.4444444444444444)) * Float32(Float32(0.25) - u))))))
end

Derivation

1. Initial program 96.0%

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

   1. lift-*.f32 N/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-*.f32 N/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. *-commutative N/A

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

   5. lower-*.f32 N/A

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

4. Applied rewrites 98.0%

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

   1. lift-*.f32 N/A

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

   2. lift-neg.f32 N/A

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

   3. distribute-lft-neg-out N/A

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

   4. distribute-rgt-neg-in N/A

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

   5. lift-log1p.f32 N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\color{blue}{\log \left(1 + \left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)\right)}\right)\right)\right) \cdot 3 \]

   6. lift-neg.f32 N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 + \color{blue}{\left(\mathsf{neg}\left(\mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)\right)}\right)\right)\right)\right) \cdot 3 \]

   7. unsub-neg N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \color{blue}{\left(1 - \mathsf{fma}\left(u, \frac{4}{3}, \frac{-1}{3}\right)\right)}\right)\right)\right) \cdot 3 \]

   8. lift-fma.f32 N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \color{blue}{\left(u \cdot \frac{4}{3} + \frac{-1}{3}\right)}\right)\right)\right)\right) \cdot 3 \]

   9. metadata-eval N/A

      \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \left(u \cdot \frac{4}{3} + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{3}\right)\right)}\right)\right)\right)\right)\right) \cdot 3 \]

   10. metadata-eval N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \left(u \cdot \frac{4}{3} + \left(\mathsf{neg}\left(\color{blue}{\frac{\frac{1}{4}}{\frac{3}{4}}}\right)\right)\right)\right)\right)\right)\right) \cdot 3 \]

   11. sub-neg N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \color{blue}{\left(u \cdot \frac{4}{3} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)}\right)\right)\right)\right) \cdot 3 \]

   12. metadata-eval N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \left(u \cdot \color{blue}{\frac{1}{\frac{3}{4}}} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)\right)\right)\right) \cdot 3 \]

   13. div-inv N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \left(\color{blue}{\frac{u}{\frac{3}{4}}} - \frac{\frac{1}{4}}{\frac{3}{4}}\right)\right)\right)\right)\right) \cdot 3 \]

   14. div-sub N/A

       \[\leadsto \left(s \cdot \left(\mathsf{neg}\left(\log \left(1 - \color{blue}{\frac{u - \frac{1}{4}}{\frac{3}{4}}}\right)\right)\right)\right) \cdot 3 \]

   15. neg-log N/A

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

   16. flip-- N/A

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

   17. associate-/r/ N/A

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

6. Applied rewrites 98.4%

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

7. Final simplification 98.4%

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

Alternative 5: 98.2% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ 3 \cdot \left(\left(-s\right) \cdot \mathsf{log1p}\left(\frac{0.25 - u}{0.75}\right)\right) \end{array} \]

FPCore

(FPCore (s u)
 :precision binary32
 (* 3.0 (* (- s) (log1p (/ (- 0.25 u) 0.75)))))

C

float code(float s, float u) {
	return 3.0f * (-s * log1pf(((0.25f - u) / 0.75f)));
}

Julia

function code(s, u)
	return Float32(Float32(3.0) * Float32(Float32(-s) * log1p(Float32(Float32(Float32(0.25) - u) / Float32(0.75)))))
end

Derivation

1. Initial program 96.0%

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

   1. lift-*.f32 N/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-*.f32 N/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. *-commutative N/A

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

   5. lower-*.f32 N/A

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

4. Applied rewrites 98.0%

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

   1. lift-neg.f32 N/A

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

   2. lift-fma.f32 N/A

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

   3. metadata-eval N/A

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

   4. distribute-rgt-in N/A

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

   5. lift-+.f32 N/A

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

   6. metadata-eval N/A

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

   7. associate-/r/ N/A

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

   8. lift-+.f32 N/A

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

   9. metadata-eval N/A

      \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\frac{1}{\frac{\frac{3}{4}}{u + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{4}\right)\right)}}}\right)\right)\right) \cdot 3 \]

   10. sub-neg N/A

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

   11. clear-num N/A

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

   12. sub-neg N/A

       \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\mathsf{neg}\left(\frac{\color{blue}{u + \left(\mathsf{neg}\left(\frac{1}{4}\right)\right)}}{\frac{3}{4}}\right)\right)\right) \cdot 3 \]

   13. metadata-eval N/A

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

   14. lift-+.f32 N/A

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

   15. distribute-neg-frac N/A

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

   16. lower-/.f32 N/A

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

   17. lift-+.f32 N/A

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

   18. distribute-neg-in N/A

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

   19. metadata-eval N/A

       \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\frac{\left(\mathsf{neg}\left(u\right)\right) + \color{blue}{\frac{1}{4}}}{\frac{3}{4}}\right)\right) \cdot 3 \]

   20. +-commutative N/A

       \[\leadsto \left(\left(\mathsf{neg}\left(s\right)\right) \cdot \mathsf{log1p}\left(\frac{\color{blue}{\frac{1}{4} + \left(\mathsf{neg}\left(u\right)\right)}}{\frac{3}{4}}\right)\right) \cdot 3 \]

   21. sub-neg N/A

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

   22. lift--.f32 98.4

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

6. Applied rewrites 98.4%

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

7. Final simplification 98.4%

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

Alternative 6: 98.2% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ s \cdot \left(\mathsf{log1p}\left(\frac{0.25 - u}{0.75}\right) \cdot -3\right) \end{array} \]

FPCore

(FPCore (s u) :precision binary32 (* s (* (log1p (/ (- 0.25 u) 0.75)) -3.0)))

C

float code(float s, float u) {
	return s * (log1pf(((0.25f - u) / 0.75f)) * -3.0f);
}

Julia

function code(s, u)
	return Float32(s * Float32(log1p(Float32(Float32(Float32(0.25) - u) / Float32(0.75))) * Float32(-3.0)))
end

Derivation

1. Initial program 96.0%

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

   1. lift-*.f32 N/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-*.f32 N/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. *-commutative N/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-*.f32 N/A

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

4. Applied rewrites 98.1%

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

   1. lift-fma.f32 N/A

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

   2. metadata-eval N/A

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

   3. metadata-eval N/A

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

   4. sub-neg N/A

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

   5. metadata-eval N/A

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

   6. div-inv N/A

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

   7. div-sub N/A

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

   8. lower-neg.f32 N/A

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

   9. sub-neg N/A

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

   10. metadata-eval N/A

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

   11. lift-+.f32 N/A

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

   12. distribute-neg-frac N/A

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

   13. lower-/.f32 N/A

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

   14. lift-+.f32 N/A

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

   15. distribute-neg-in N/A

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

   16. metadata-eval N/A

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

   17. +-commutative N/A

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

   18. sub-neg N/A

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

   19. lift--.f32 98.3

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

6. Applied rewrites 98.3%

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

7. Final simplification 98.3%

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

Alternative 7: 97.9% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ s \cdot \left(-3 \cdot \mathsf{log1p}\left(\mathsf{fma}\left(u, -1.3333333333333333, 0.3333333333333333\right)\right)\right) \end{array} \]

FPCore

(FPCore (s u)
 :precision binary32
 (* s (* -3.0 (log1p (fma u -1.3333333333333333 0.3333333333333333)))))

C

float code(float s, float u) {
	return s * (-3.0f * log1pf(fmaf(u, -1.3333333333333333f, 0.3333333333333333f)));
}

Julia

function code(s, u)
	return Float32(s * Float32(Float32(-3.0) * log1p(fma(u, Float32(-1.3333333333333333), Float32(0.3333333333333333)))))
end

Derivation

1. Initial program 96.0%

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

   1. lift-*.f32 N/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-*.f32 N/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. *-commutative N/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-*.f32 N/A

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

4. Applied rewrites 98.1%

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

   1. lift-neg.f32 N/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.f32 N/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-in N/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. distribute-rgt-neg-in N/A

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

   5. metadata-eval N/A

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

   6. metadata-eval N/A

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

   7. metadata-eval N/A

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

   8. metadata-eval N/A

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

   9. lower-fma.f32 N/A

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

   10. metadata-eval N/A

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

   11. metadata-eval 98.1

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

6. Applied rewrites 98.1%

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

7. Final simplification 98.1%

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

Alternative 8: 97.9% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \left(s \cdot -3\right) \cdot \mathsf{log1p}\left(\mathsf{fma}\left(-1.3333333333333333, u, 0.3333333333333333\right)\right) \end{array} \]

FPCore

(FPCore (s u)
 :precision binary32
 (* (* s -3.0) (log1p (fma -1.3333333333333333 u 0.3333333333333333))))

C

float code(float s, float u) {
	return (s * -3.0f) * log1pf(fmaf(-1.3333333333333333f, u, 0.3333333333333333f));
}

Julia

function code(s, u)
	return Float32(Float32(s * Float32(-3.0)) * log1p(fma(Float32(-1.3333333333333333), u, Float32(0.3333333333333333))))
end

Derivation

1. Initial program 96.0%

   \[\left(3 \cdot s\right) \cdot \log \left(\frac{1}{1 - \frac{u - 0.25}{0.75}}\right) \]
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-rec N/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-out N/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-in N/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-in N/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-eval N/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-*.f32 N/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. *-commutative N/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-*.f32 N/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-neg N/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.f32 N/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-in N/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-eval N/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-neg N/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-in N/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-eval N/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-eval N/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.f32 98.0

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

5. Applied rewrites 98.0%

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

Alternative 9: 30.0% accurate, 10.7× speedup

Math

\[\begin{array}{l} \\ s \cdot \left(-3 \cdot \left(-u\right)\right) \end{array} \]

FPCore

(FPCore (s u) :precision binary32 (* s (* -3.0 (- u))))

C

float code(float s, float u) {
	return s * (-3.0f * -u);
}

Fortran

real(4) function code(s, u)
    real(4), intent (in) :: s
    real(4), intent (in) :: u
    code = s * ((-3.0e0) * -u)
end function

Julia

function code(s, u)
	return Float32(s * Float32(Float32(-3.0) * Float32(-u)))
end

MATLAB

function tmp = code(s, u)
	tmp = s * (single(-3.0) * -u);
end

Derivation

1. Initial program 96.0%

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

   1. lift-*.f32 N/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-*.f32 N/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. *-commutative N/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-*.f32 N/A

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

4. Applied rewrites 98.1%

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

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-neg N/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-neg N/A

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

   3. lower--.f32 N/A

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

   4. lower-log.f32 25.8

      \[\leadsto \left(-3 \cdot \left(\color{blue}{\log 1.3333333333333333} - u\right)\right) \cdot s \]

7. Applied rewrites 25.8%

   \[\leadsto \left(-3 \cdot \color{blue}{\left(\log 1.3333333333333333 - u\right)}\right) \cdot s \]

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

10. Applied rewrites 30.0%

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

11. Final simplification 30.0%

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

Reproduce

herbie shell --seed 2024231 
(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))))))