Rust f32::atanh

Percentage Accurate: 99.8% → 99.8%
Time: 2.2s
Alternatives: 9
Speedup: 1.0×

Specification

?
\[\begin{array}{l} \\ 0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \end{array} \]
(FPCore (x) :precision binary32 (* 0.5 (log1p (/ (* 2.0 x) (- 1.0 x)))))
float code(float x) {
	return 0.5f * log1pf(((2.0f * x) / (1.0f - x)));
}
function code(x)
	return Float32(Float32(0.5) * log1p(Float32(Float32(Float32(2.0) * x) / Float32(Float32(1.0) - x))))
end
\begin{array}{l}

\\
0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right)
\end{array}

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 9 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: 99.8% accurate, 1.0× speedup?

\[\begin{array}{l} \\ 0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \end{array} \]
(FPCore (x) :precision binary32 (* 0.5 (log1p (/ (* 2.0 x) (- 1.0 x)))))
float code(float x) {
	return 0.5f * log1pf(((2.0f * x) / (1.0f - x)));
}
function code(x)
	return Float32(Float32(0.5) * log1p(Float32(Float32(Float32(2.0) * x) / Float32(Float32(1.0) - x))))
end
\begin{array}{l}

\\
0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right)
\end{array}

Alternative 1: 99.8% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \mathsf{log1p}\left(\frac{x + x}{1 - x}\right) \cdot 0.5 \end{array} \]
(FPCore (x) :precision binary32 (* (log1p (/ (+ x x) (- 1.0 x))) 0.5))
float code(float x) {
	return log1pf(((x + x) / (1.0f - x))) * 0.5f;
}
function code(x)
	return Float32(log1p(Float32(Float32(x + x) / Float32(Float32(1.0) - x))) * Float32(0.5))
end
\begin{array}{l}

\\
\mathsf{log1p}\left(\frac{x + x}{1 - x}\right) \cdot 0.5
\end{array}
Derivation
  1. Initial program 99.8%

    \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
  2. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \color{blue}{\frac{1}{2} \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right)} \]
    2. lift-log1p.f32N/A

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

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

      \[\leadsto \frac{1}{2} \cdot \log \left(1 + \frac{2 \cdot x}{\color{blue}{1 - x}}\right) \]
    5. lift-/.f32N/A

      \[\leadsto \frac{1}{2} \cdot \log \left(1 + \color{blue}{\frac{2 \cdot x}{1 - x}}\right) \]
    6. *-commutativeN/A

      \[\leadsto \color{blue}{\log \left(1 + \frac{2 \cdot x}{1 - x}\right) \cdot \frac{1}{2}} \]
    7. lower-*.f32N/A

      \[\leadsto \color{blue}{\log \left(1 + \frac{2 \cdot x}{1 - x}\right) \cdot \frac{1}{2}} \]
    8. lift-/.f32N/A

      \[\leadsto \log \left(1 + \color{blue}{\frac{2 \cdot x}{1 - x}}\right) \cdot \frac{1}{2} \]
    9. lift-*.f32N/A

      \[\leadsto \log \left(1 + \frac{\color{blue}{2 \cdot x}}{1 - x}\right) \cdot \frac{1}{2} \]
    10. lift--.f32N/A

      \[\leadsto \log \left(1 + \frac{2 \cdot x}{\color{blue}{1 - x}}\right) \cdot \frac{1}{2} \]
    11. lift-log1p.f3299.8

      \[\leadsto \color{blue}{\mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right)} \cdot 0.5 \]
    12. lift-*.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\color{blue}{2 \cdot x}}{1 - x}\right) \cdot \frac{1}{2} \]
    13. count-2-revN/A

      \[\leadsto \mathsf{log1p}\left(\frac{\color{blue}{x + x}}{1 - x}\right) \cdot \frac{1}{2} \]
    14. lower-+.f3299.8

      \[\leadsto \mathsf{log1p}\left(\frac{\color{blue}{x + x}}{1 - x}\right) \cdot 0.5 \]
  3. Applied rewrites99.8%

    \[\leadsto \color{blue}{\mathsf{log1p}\left(\frac{x + x}{1 - x}\right) \cdot 0.5} \]
  4. Add Preprocessing

Alternative 2: 99.2% accurate, 3.2× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(x \cdot x, 0.14285714285714285, 0.2\right), x \cdot x, 0.3333333333333333\right) \cdot x\right) \cdot x, x, x\right) \end{array} \]
(FPCore (x)
 :precision binary32
 (fma
  (*
   (* (fma (fma (* x x) 0.14285714285714285 0.2) (* x x) 0.3333333333333333) x)
   x)
  x
  x))
float code(float x) {
	return fmaf(((fmaf(fmaf((x * x), 0.14285714285714285f, 0.2f), (x * x), 0.3333333333333333f) * x) * x), x, x);
}
function code(x)
	return fma(Float32(Float32(fma(fma(Float32(x * x), Float32(0.14285714285714285), Float32(0.2)), Float32(x * x), Float32(0.3333333333333333)) * x) * x), x, x)
end
\begin{array}{l}

\\
\mathsf{fma}\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(x \cdot x, 0.14285714285714285, 0.2\right), x \cdot x, 0.3333333333333333\right) \cdot x\right) \cdot x, x, x\right)
\end{array}
Derivation
  1. Initial program 99.8%

    \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
  2. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \color{blue}{\frac{1}{2} \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right)} \]
    2. lift-log1p.f32N/A

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

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

      \[\leadsto \frac{1}{2} \cdot \log \left(1 + \frac{2 \cdot x}{\color{blue}{1 - x}}\right) \]
    5. lift-/.f32N/A

      \[\leadsto \frac{1}{2} \cdot \log \left(1 + \color{blue}{\frac{2 \cdot x}{1 - x}}\right) \]
    6. *-commutativeN/A

      \[\leadsto \color{blue}{\log \left(1 + \frac{2 \cdot x}{1 - x}\right) \cdot \frac{1}{2}} \]
    7. lower-*.f32N/A

      \[\leadsto \color{blue}{\log \left(1 + \frac{2 \cdot x}{1 - x}\right) \cdot \frac{1}{2}} \]
    8. lift-/.f32N/A

      \[\leadsto \log \left(1 + \color{blue}{\frac{2 \cdot x}{1 - x}}\right) \cdot \frac{1}{2} \]
    9. lift-*.f32N/A

      \[\leadsto \log \left(1 + \frac{\color{blue}{2 \cdot x}}{1 - x}\right) \cdot \frac{1}{2} \]
    10. lift--.f32N/A

      \[\leadsto \log \left(1 + \frac{2 \cdot x}{\color{blue}{1 - x}}\right) \cdot \frac{1}{2} \]
    11. lift-log1p.f3299.8

      \[\leadsto \color{blue}{\mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right)} \cdot 0.5 \]
    12. lift-*.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\color{blue}{2 \cdot x}}{1 - x}\right) \cdot \frac{1}{2} \]
    13. count-2-revN/A

      \[\leadsto \mathsf{log1p}\left(\frac{\color{blue}{x + x}}{1 - x}\right) \cdot \frac{1}{2} \]
    14. lower-+.f3299.8

      \[\leadsto \mathsf{log1p}\left(\frac{\color{blue}{x + x}}{1 - x}\right) \cdot 0.5 \]
  3. Applied rewrites99.8%

    \[\leadsto \color{blue}{\mathsf{log1p}\left(\frac{x + x}{1 - x}\right) \cdot 0.5} \]
  4. Step-by-step derivation
    1. lift-+.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\color{blue}{x + x}}{1 - x}\right) \cdot \frac{1}{2} \]
    2. lift--.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{x + x}{\color{blue}{1 - x}}\right) \cdot \frac{1}{2} \]
    3. lift-/.f32N/A

      \[\leadsto \mathsf{log1p}\left(\color{blue}{\frac{x + x}{1 - x}}\right) \cdot \frac{1}{2} \]
    4. div-addN/A

      \[\leadsto \mathsf{log1p}\left(\color{blue}{\frac{x}{1 - x} + \frac{x}{1 - x}}\right) \cdot \frac{1}{2} \]
    5. frac-addN/A

      \[\leadsto \mathsf{log1p}\left(\color{blue}{\frac{x \cdot \left(1 - x\right) + \left(1 - x\right) \cdot x}{\left(1 - x\right) \cdot \left(1 - x\right)}}\right) \cdot \frac{1}{2} \]
    6. lower-/.f32N/A

      \[\leadsto \mathsf{log1p}\left(\color{blue}{\frac{x \cdot \left(1 - x\right) + \left(1 - x\right) \cdot x}{\left(1 - x\right) \cdot \left(1 - x\right)}}\right) \cdot \frac{1}{2} \]
    7. lower-fma.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\color{blue}{\mathsf{fma}\left(x, 1 - x, \left(1 - x\right) \cdot x\right)}}{\left(1 - x\right) \cdot \left(1 - x\right)}\right) \cdot \frac{1}{2} \]
    8. lift--.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\mathsf{fma}\left(x, \color{blue}{1 - x}, \left(1 - x\right) \cdot x\right)}{\left(1 - x\right) \cdot \left(1 - x\right)}\right) \cdot \frac{1}{2} \]
    9. lower-*.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\mathsf{fma}\left(x, 1 - x, \color{blue}{\left(1 - x\right) \cdot x}\right)}{\left(1 - x\right) \cdot \left(1 - x\right)}\right) \cdot \frac{1}{2} \]
    10. lift--.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\mathsf{fma}\left(x, 1 - x, \color{blue}{\left(1 - x\right)} \cdot x\right)}{\left(1 - x\right) \cdot \left(1 - x\right)}\right) \cdot \frac{1}{2} \]
    11. lower-*.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\mathsf{fma}\left(x, 1 - x, \left(1 - x\right) \cdot x\right)}{\color{blue}{\left(1 - x\right) \cdot \left(1 - x\right)}}\right) \cdot \frac{1}{2} \]
    12. lift--.f32N/A

      \[\leadsto \mathsf{log1p}\left(\frac{\mathsf{fma}\left(x, 1 - x, \left(1 - x\right) \cdot x\right)}{\color{blue}{\left(1 - x\right)} \cdot \left(1 - x\right)}\right) \cdot \frac{1}{2} \]
    13. lift--.f3299.7

      \[\leadsto \mathsf{log1p}\left(\frac{\mathsf{fma}\left(x, 1 - x, \left(1 - x\right) \cdot x\right)}{\left(1 - x\right) \cdot \color{blue}{\left(1 - x\right)}}\right) \cdot 0.5 \]
  5. Applied rewrites99.7%

    \[\leadsto \mathsf{log1p}\left(\color{blue}{\frac{\mathsf{fma}\left(x, 1 - x, \left(1 - x\right) \cdot x\right)}{\left(1 - x\right) \cdot \left(1 - x\right)}}\right) \cdot 0.5 \]
  6. Taylor expanded in x around 0

    \[\leadsto \color{blue}{x \cdot \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + {x}^{2} \cdot \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right)\right)\right)} \]
  7. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto x \cdot \left(1 + \left(\frac{1}{3} + {x}^{2} \cdot \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right)\right) \cdot \color{blue}{{x}^{2}}\right) \]
    2. *-commutativeN/A

      \[\leadsto x \cdot \left(1 + \left(\frac{1}{3} + \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right) \cdot {x}^{2}\right) \cdot {x}^{2}\right) \]
    3. *-commutativeN/A

      \[\leadsto x \cdot \left(1 + \left(\frac{1}{3} + \left(\frac{1}{5} + {x}^{2} \cdot \frac{1}{7}\right) \cdot {x}^{2}\right) \cdot {x}^{2}\right) \]
    4. pow2N/A

      \[\leadsto x \cdot \left(1 + \left(\frac{1}{3} + \left(\frac{1}{5} + \left(x \cdot x\right) \cdot \frac{1}{7}\right) \cdot {x}^{2}\right) \cdot {x}^{2}\right) \]
    5. +-commutativeN/A

      \[\leadsto x \cdot \left(1 + \left(\frac{1}{3} + \left(\left(x \cdot x\right) \cdot \frac{1}{7} + \frac{1}{5}\right) \cdot {x}^{2}\right) \cdot {x}^{2}\right) \]
    6. pow2N/A

      \[\leadsto x \cdot \left(1 + \left(\frac{1}{3} + \left(\left(x \cdot x\right) \cdot \frac{1}{7} + \frac{1}{5}\right) \cdot \left(x \cdot x\right)\right) \cdot {x}^{2}\right) \]
    7. +-commutativeN/A

      \[\leadsto x \cdot \left(1 + \left(\left(\left(x \cdot x\right) \cdot \frac{1}{7} + \frac{1}{5}\right) \cdot \left(x \cdot x\right) + \frac{1}{3}\right) \cdot {\color{blue}{x}}^{2}\right) \]
    8. pow2N/A

      \[\leadsto x \cdot \left(1 + \left(\left(\left(x \cdot x\right) \cdot \frac{1}{7} + \frac{1}{5}\right) \cdot \left(x \cdot x\right) + \frac{1}{3}\right) \cdot \left(x \cdot \color{blue}{x}\right)\right) \]
    9. associate-*l*N/A

      \[\leadsto x \cdot \left(1 + \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{7} + \frac{1}{5}\right) \cdot \left(x \cdot x\right) + \frac{1}{3}\right) \cdot x\right) \cdot \color{blue}{x}\right) \]
  8. Applied rewrites99.2%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\mathsf{fma}\left(\mathsf{fma}\left(x \cdot x, 0.14285714285714285, 0.2\right), x \cdot x, 0.3333333333333333\right) \cdot x\right) \cdot x, x, x\right)} \]
  9. Add Preprocessing

Alternative 3: 99.1% accurate, 3.2× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.14285714285714285, x \cdot x, 0.2\right), x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x \end{array} \]
(FPCore (x)
 :precision binary32
 (*
  (fma
   (fma (fma 0.14285714285714285 (* x x) 0.2) (* x x) 0.3333333333333333)
   (* x x)
   1.0)
  x))
float code(float x) {
	return fmaf(fmaf(fmaf(0.14285714285714285f, (x * x), 0.2f), (x * x), 0.3333333333333333f), (x * x), 1.0f) * x;
}
function code(x)
	return Float32(fma(fma(fma(Float32(0.14285714285714285), Float32(x * x), Float32(0.2)), Float32(x * x), Float32(0.3333333333333333)), Float32(x * x), Float32(1.0)) * x)
end
\begin{array}{l}

\\
\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.14285714285714285, x \cdot x, 0.2\right), x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x
\end{array}
Derivation
  1. Initial program 99.8%

    \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
  2. Taylor expanded in x around 0

    \[\leadsto \color{blue}{x \cdot \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + {x}^{2} \cdot \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right)\right)\right)} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + {x}^{2} \cdot \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right)\right)\right) \cdot \color{blue}{x} \]
    2. lower-*.f32N/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + {x}^{2} \cdot \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right)\right)\right) \cdot \color{blue}{x} \]
  4. Applied rewrites99.1%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.14285714285714285, x \cdot x, 0.2\right), x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x} \]
  5. Add Preprocessing

Alternative 4: 99.0% accurate, 4.2× speedup?

\[\begin{array}{l} \\ \left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot \left(x \cdot x\right) + x \end{array} \]
(FPCore (x)
 :precision binary32
 (+ (* (* (fma (* x x) 0.2 0.3333333333333333) x) (* x x)) x))
float code(float x) {
	return ((fmaf((x * x), 0.2f, 0.3333333333333333f) * x) * (x * x)) + x;
}
function code(x)
	return Float32(Float32(Float32(fma(Float32(x * x), Float32(0.2), Float32(0.3333333333333333)) * x) * Float32(x * x)) + x)
end
\begin{array}{l}

\\
\left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot \left(x \cdot x\right) + x
\end{array}
Derivation
  1. Initial program 99.8%

    \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
  2. Taylor expanded in x around 0

    \[\leadsto \color{blue}{x \cdot \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot \color{blue}{x} \]
    2. lower-*.f32N/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot \color{blue}{x} \]
    3. +-commutativeN/A

      \[\leadsto \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) + 1\right) \cdot x \]
    4. *-commutativeN/A

      \[\leadsto \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2} + 1\right) \cdot x \]
    5. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}, {x}^{2}, 1\right) \cdot x \]
    6. +-commutativeN/A

      \[\leadsto \mathsf{fma}\left(\frac{1}{5} \cdot {x}^{2} + \frac{1}{3}, {x}^{2}, 1\right) \cdot x \]
    7. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, {x}^{2}, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    8. unpow2N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    9. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    10. unpow2N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), x \cdot x, 1\right) \cdot x \]
    11. lower-*.f3298.9

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.2, x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x \]
  4. Applied rewrites98.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(0.2, x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x} \]
  5. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), x \cdot x, 1\right) \cdot \color{blue}{x} \]
    2. lift-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), x \cdot x, 1\right) \cdot x \]
    3. lift-fma.f32N/A

      \[\leadsto \left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right) \cdot \left(x \cdot x\right) + 1\right) \cdot x \]
    4. lift-*.f32N/A

      \[\leadsto \left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right) \cdot \left(x \cdot x\right) + 1\right) \cdot x \]
    5. lift-fma.f32N/A

      \[\leadsto \left(\left(\frac{1}{5} \cdot \left(x \cdot x\right) + \frac{1}{3}\right) \cdot \left(x \cdot x\right) + 1\right) \cdot x \]
    6. +-commutativeN/A

      \[\leadsto \left(1 + \left(\frac{1}{5} \cdot \left(x \cdot x\right) + \frac{1}{3}\right) \cdot \left(x \cdot x\right)\right) \cdot x \]
    7. +-commutativeN/A

      \[\leadsto \left(1 + \left(\frac{1}{3} + \frac{1}{5} \cdot \left(x \cdot x\right)\right) \cdot \left(x \cdot x\right)\right) \cdot x \]
    8. pow2N/A

      \[\leadsto \left(1 + \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot \left(x \cdot x\right)\right) \cdot x \]
    9. pow2N/A

      \[\leadsto \left(1 + \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2}\right) \cdot x \]
    10. *-commutativeN/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot x \]
    11. *-commutativeN/A

      \[\leadsto x \cdot \color{blue}{\left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)} \]
    12. distribute-lft-inN/A

      \[\leadsto x \cdot 1 + \color{blue}{x \cdot \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)} \]
    13. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(x, \color{blue}{1}, x \cdot \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)\right) \]
    14. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(x, 1, x \cdot \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)\right) \]
    15. *-commutativeN/A

      \[\leadsto \mathsf{fma}\left(x, 1, x \cdot \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2}\right)\right) \]
  6. Applied rewrites99.0%

    \[\leadsto \mathsf{fma}\left(x, \color{blue}{1}, x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot x\right)\right) \]
  7. Step-by-step derivation
    1. lift-fma.f32N/A

      \[\leadsto x \cdot 1 + \color{blue}{x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right)} \]
    2. *-rgt-identityN/A

      \[\leadsto x + \color{blue}{x} \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \]
    3. lift-*.f32N/A

      \[\leadsto x + x \cdot \color{blue}{\left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right)} \]
    4. lift-*.f32N/A

      \[\leadsto x + x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot \color{blue}{x}\right) \]
    5. lift-*.f32N/A

      \[\leadsto x + x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \]
    6. lift-*.f32N/A

      \[\leadsto x + x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \]
    7. lift-fma.f32N/A

      \[\leadsto x + x \cdot \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) \]
    8. +-commutativeN/A

      \[\leadsto x \cdot \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) + \color{blue}{x} \]
    9. *-commutativeN/A

      \[\leadsto \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) \cdot x + x \]
    10. associate-*l*N/A

      \[\leadsto \left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot \left(x \cdot x\right)\right) \cdot x + x \]
    11. +-commutativeN/A

      \[\leadsto \left(\left(\frac{1}{3} + \left(x \cdot x\right) \cdot \frac{1}{5}\right) \cdot \left(x \cdot x\right)\right) \cdot x + x \]
    12. pow2N/A

      \[\leadsto \left(\left(\frac{1}{3} + {x}^{2} \cdot \frac{1}{5}\right) \cdot \left(x \cdot x\right)\right) \cdot x + x \]
    13. *-commutativeN/A

      \[\leadsto \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot \left(x \cdot x\right)\right) \cdot x + x \]
    14. pow2N/A

      \[\leadsto \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2}\right) \cdot x + x \]
    15. *-commutativeN/A

      \[\leadsto \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot x + x \]
    16. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right), \color{blue}{x}, x\right) \]
  8. Applied rewrites99.0%

    \[\leadsto \mathsf{fma}\left(\left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot x, \color{blue}{x}, x\right) \]
  9. Step-by-step derivation
    1. lift-fma.f32N/A

      \[\leadsto \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \cdot x + \color{blue}{x} \]
    2. lift-*.f32N/A

      \[\leadsto \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \cdot x + x \]
    3. lift-*.f32N/A

      \[\leadsto \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \cdot x + x \]
    4. lift-fma.f32N/A

      \[\leadsto \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) \cdot x + x \]
    5. lift-*.f32N/A

      \[\leadsto \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) \cdot x + x \]
    6. lower-+.f32N/A

      \[\leadsto \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) \cdot x + \color{blue}{x} \]
    7. associate-*l*N/A

      \[\leadsto \left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot \left(x \cdot x\right) + x \]
    8. pow2N/A

      \[\leadsto \left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot {x}^{2} + x \]
    9. lower-*.f32N/A

      \[\leadsto \left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot {x}^{2} + x \]
    10. lift-*.f32N/A

      \[\leadsto \left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot {x}^{2} + x \]
    11. lift-fma.f32N/A

      \[\leadsto \left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot {x}^{2} + x \]
    12. lift-*.f32N/A

      \[\leadsto \left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot {x}^{2} + x \]
    13. pow2N/A

      \[\leadsto \left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot \left(x \cdot x\right) + x \]
    14. lift-*.f3299.0

      \[\leadsto \left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot \left(x \cdot x\right) + x \]
  10. Applied rewrites99.0%

    \[\leadsto \left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot \left(x \cdot x\right) + \color{blue}{x} \]
  11. Add Preprocessing

Alternative 5: 99.0% accurate, 4.5× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(\left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot x, x, x\right) \end{array} \]
(FPCore (x)
 :precision binary32
 (fma (* (* (fma (* x x) 0.2 0.3333333333333333) x) x) x x))
float code(float x) {
	return fmaf(((fmaf((x * x), 0.2f, 0.3333333333333333f) * x) * x), x, x);
}
function code(x)
	return fma(Float32(Float32(fma(Float32(x * x), Float32(0.2), Float32(0.3333333333333333)) * x) * x), x, x)
end
\begin{array}{l}

\\
\mathsf{fma}\left(\left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot x, x, x\right)
\end{array}
Derivation
  1. Initial program 99.8%

    \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
  2. Taylor expanded in x around 0

    \[\leadsto \color{blue}{x \cdot \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot \color{blue}{x} \]
    2. lower-*.f32N/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot \color{blue}{x} \]
    3. +-commutativeN/A

      \[\leadsto \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) + 1\right) \cdot x \]
    4. *-commutativeN/A

      \[\leadsto \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2} + 1\right) \cdot x \]
    5. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}, {x}^{2}, 1\right) \cdot x \]
    6. +-commutativeN/A

      \[\leadsto \mathsf{fma}\left(\frac{1}{5} \cdot {x}^{2} + \frac{1}{3}, {x}^{2}, 1\right) \cdot x \]
    7. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, {x}^{2}, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    8. unpow2N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    9. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    10. unpow2N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), x \cdot x, 1\right) \cdot x \]
    11. lower-*.f3298.9

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.2, x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x \]
  4. Applied rewrites98.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(0.2, x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x} \]
  5. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), x \cdot x, 1\right) \cdot \color{blue}{x} \]
    2. lift-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), x \cdot x, 1\right) \cdot x \]
    3. lift-fma.f32N/A

      \[\leadsto \left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right) \cdot \left(x \cdot x\right) + 1\right) \cdot x \]
    4. lift-*.f32N/A

      \[\leadsto \left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right) \cdot \left(x \cdot x\right) + 1\right) \cdot x \]
    5. lift-fma.f32N/A

      \[\leadsto \left(\left(\frac{1}{5} \cdot \left(x \cdot x\right) + \frac{1}{3}\right) \cdot \left(x \cdot x\right) + 1\right) \cdot x \]
    6. +-commutativeN/A

      \[\leadsto \left(1 + \left(\frac{1}{5} \cdot \left(x \cdot x\right) + \frac{1}{3}\right) \cdot \left(x \cdot x\right)\right) \cdot x \]
    7. +-commutativeN/A

      \[\leadsto \left(1 + \left(\frac{1}{3} + \frac{1}{5} \cdot \left(x \cdot x\right)\right) \cdot \left(x \cdot x\right)\right) \cdot x \]
    8. pow2N/A

      \[\leadsto \left(1 + \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot \left(x \cdot x\right)\right) \cdot x \]
    9. pow2N/A

      \[\leadsto \left(1 + \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2}\right) \cdot x \]
    10. *-commutativeN/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot x \]
    11. *-commutativeN/A

      \[\leadsto x \cdot \color{blue}{\left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)} \]
    12. distribute-lft-inN/A

      \[\leadsto x \cdot 1 + \color{blue}{x \cdot \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)} \]
    13. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(x, \color{blue}{1}, x \cdot \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)\right) \]
    14. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(x, 1, x \cdot \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)\right) \]
    15. *-commutativeN/A

      \[\leadsto \mathsf{fma}\left(x, 1, x \cdot \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2}\right)\right) \]
  6. Applied rewrites99.0%

    \[\leadsto \mathsf{fma}\left(x, \color{blue}{1}, x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot x\right)\right) \]
  7. Step-by-step derivation
    1. lift-fma.f32N/A

      \[\leadsto x \cdot 1 + \color{blue}{x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right)} \]
    2. *-rgt-identityN/A

      \[\leadsto x + \color{blue}{x} \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \]
    3. lift-*.f32N/A

      \[\leadsto x + x \cdot \color{blue}{\left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right)} \]
    4. lift-*.f32N/A

      \[\leadsto x + x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot \color{blue}{x}\right) \]
    5. lift-*.f32N/A

      \[\leadsto x + x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \]
    6. lift-*.f32N/A

      \[\leadsto x + x \cdot \left(\left(\mathsf{fma}\left(x \cdot x, \frac{1}{5}, \frac{1}{3}\right) \cdot x\right) \cdot x\right) \]
    7. lift-fma.f32N/A

      \[\leadsto x + x \cdot \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) \]
    8. +-commutativeN/A

      \[\leadsto x \cdot \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) + \color{blue}{x} \]
    9. *-commutativeN/A

      \[\leadsto \left(\left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot x\right) \cdot x\right) \cdot x + x \]
    10. associate-*l*N/A

      \[\leadsto \left(\left(\left(x \cdot x\right) \cdot \frac{1}{5} + \frac{1}{3}\right) \cdot \left(x \cdot x\right)\right) \cdot x + x \]
    11. +-commutativeN/A

      \[\leadsto \left(\left(\frac{1}{3} + \left(x \cdot x\right) \cdot \frac{1}{5}\right) \cdot \left(x \cdot x\right)\right) \cdot x + x \]
    12. pow2N/A

      \[\leadsto \left(\left(\frac{1}{3} + {x}^{2} \cdot \frac{1}{5}\right) \cdot \left(x \cdot x\right)\right) \cdot x + x \]
    13. *-commutativeN/A

      \[\leadsto \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot \left(x \cdot x\right)\right) \cdot x + x \]
    14. pow2N/A

      \[\leadsto \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2}\right) \cdot x + x \]
    15. *-commutativeN/A

      \[\leadsto \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot x + x \]
    16. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right), \color{blue}{x}, x\right) \]
  8. Applied rewrites99.0%

    \[\leadsto \mathsf{fma}\left(\left(\mathsf{fma}\left(x \cdot x, 0.2, 0.3333333333333333\right) \cdot x\right) \cdot x, \color{blue}{x}, x\right) \]
  9. Add Preprocessing

Alternative 6: 98.9% accurate, 4.5× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(\mathsf{fma}\left(0.2, x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x \end{array} \]
(FPCore (x)
 :precision binary32
 (* (fma (fma 0.2 (* x x) 0.3333333333333333) (* x x) 1.0) x))
float code(float x) {
	return fmaf(fmaf(0.2f, (x * x), 0.3333333333333333f), (x * x), 1.0f) * x;
}
function code(x)
	return Float32(fma(fma(Float32(0.2), Float32(x * x), Float32(0.3333333333333333)), Float32(x * x), Float32(1.0)) * x)
end
\begin{array}{l}

\\
\mathsf{fma}\left(\mathsf{fma}\left(0.2, x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x
\end{array}
Derivation
  1. Initial program 99.8%

    \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
  2. Taylor expanded in x around 0

    \[\leadsto \color{blue}{x \cdot \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right)} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot \color{blue}{x} \]
    2. lower-*.f32N/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right)\right) \cdot \color{blue}{x} \]
    3. +-commutativeN/A

      \[\leadsto \left({x}^{2} \cdot \left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) + 1\right) \cdot x \]
    4. *-commutativeN/A

      \[\leadsto \left(\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}\right) \cdot {x}^{2} + 1\right) \cdot x \]
    5. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(\frac{1}{3} + \frac{1}{5} \cdot {x}^{2}, {x}^{2}, 1\right) \cdot x \]
    6. +-commutativeN/A

      \[\leadsto \mathsf{fma}\left(\frac{1}{5} \cdot {x}^{2} + \frac{1}{3}, {x}^{2}, 1\right) \cdot x \]
    7. lower-fma.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, {x}^{2}, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    8. unpow2N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    9. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), {x}^{2}, 1\right) \cdot x \]
    10. unpow2N/A

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(\frac{1}{5}, x \cdot x, \frac{1}{3}\right), x \cdot x, 1\right) \cdot x \]
    11. lower-*.f3298.9

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(0.2, x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x \]
  4. Applied rewrites98.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(0.2, x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x} \]
  5. Add Preprocessing

Alternative 7: 98.4% accurate, 6.6× speedup?

\[\begin{array}{l} \\ \left(\left(0.3333333333333333 \cdot x\right) \cdot x\right) \cdot x + x \end{array} \]
(FPCore (x) :precision binary32 (+ (* (* (* 0.3333333333333333 x) x) x) x))
float code(float x) {
	return (((0.3333333333333333f * x) * x) * x) + x;
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(4) function code(x)
use fmin_fmax_functions
    real(4), intent (in) :: x
    code = (((0.3333333333333333e0 * x) * x) * x) + x
end function
function code(x)
	return Float32(Float32(Float32(Float32(Float32(0.3333333333333333) * x) * x) * x) + x)
end
function tmp = code(x)
	tmp = (((single(0.3333333333333333) * x) * x) * x) + x;
end
\begin{array}{l}

\\
\left(\left(0.3333333333333333 \cdot x\right) \cdot x\right) \cdot x + x
\end{array}
Derivation
  1. Initial program 99.8%

    \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
  2. Taylor expanded in x around 0

    \[\leadsto \color{blue}{x \cdot \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + {x}^{2} \cdot \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right)\right)\right)} \]
  3. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + {x}^{2} \cdot \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right)\right)\right) \cdot \color{blue}{x} \]
    2. lower-*.f32N/A

      \[\leadsto \left(1 + {x}^{2} \cdot \left(\frac{1}{3} + {x}^{2} \cdot \left(\frac{1}{5} + \frac{1}{7} \cdot {x}^{2}\right)\right)\right) \cdot \color{blue}{x} \]
  4. Applied rewrites99.1%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.14285714285714285, x \cdot x, 0.2\right), x \cdot x, 0.3333333333333333\right), x \cdot x, 1\right) \cdot x} \]
  5. Applied rewrites99.2%

    \[\leadsto \mathsf{fma}\left(x, \color{blue}{1}, x \cdot \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(x \cdot x, 0.14285714285714285, 0.2\right), x \cdot x, 0.3333333333333333\right) \cdot x\right) \cdot x\right)\right) \]
  6. Taylor expanded in x around 0

    \[\leadsto \mathsf{fma}\left(x, 1, x \cdot \left(\left(\frac{1}{3} \cdot x\right) \cdot x\right)\right) \]
  7. Step-by-step derivation
    1. Applied rewrites98.4%

      \[\leadsto \mathsf{fma}\left(x, 1, x \cdot \left(\left(0.3333333333333333 \cdot x\right) \cdot x\right)\right) \]
    2. Step-by-step derivation
      1. lift-fma.f32N/A

        \[\leadsto x \cdot 1 + \color{blue}{x \cdot \left(\left(\frac{1}{3} \cdot x\right) \cdot x\right)} \]
      2. *-rgt-identityN/A

        \[\leadsto x + \color{blue}{x} \cdot \left(\left(\frac{1}{3} \cdot x\right) \cdot x\right) \]
      3. +-commutativeN/A

        \[\leadsto x \cdot \left(\left(\frac{1}{3} \cdot x\right) \cdot x\right) + \color{blue}{x} \]
      4. lower-+.f3298.4

        \[\leadsto x \cdot \left(\left(0.3333333333333333 \cdot x\right) \cdot x\right) + \color{blue}{x} \]
    3. Applied rewrites98.4%

      \[\leadsto \left(\left(0.3333333333333333 \cdot x\right) \cdot x\right) \cdot x + \color{blue}{x} \]
    4. Add Preprocessing

    Alternative 8: 98.4% accurate, 7.4× speedup?

    \[\begin{array}{l} \\ \mathsf{fma}\left(\left(x \cdot x\right) \cdot x, 0.3333333333333333, x\right) \end{array} \]
    (FPCore (x) :precision binary32 (fma (* (* x x) x) 0.3333333333333333 x))
    float code(float x) {
    	return fmaf(((x * x) * x), 0.3333333333333333f, x);
    }
    
    function code(x)
    	return fma(Float32(Float32(x * x) * x), Float32(0.3333333333333333), x)
    end
    
    \begin{array}{l}
    
    \\
    \mathsf{fma}\left(\left(x \cdot x\right) \cdot x, 0.3333333333333333, x\right)
    \end{array}
    
    Derivation
    1. Initial program 99.8%

      \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
    2. Taylor expanded in x around 0

      \[\leadsto \color{blue}{x \cdot \left(1 + \frac{1}{3} \cdot {x}^{2}\right)} \]
    3. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(1 + \frac{1}{3} \cdot {x}^{2}\right) \cdot \color{blue}{x} \]
      2. lower-*.f32N/A

        \[\leadsto \left(1 + \frac{1}{3} \cdot {x}^{2}\right) \cdot \color{blue}{x} \]
      3. +-commutativeN/A

        \[\leadsto \left(\frac{1}{3} \cdot {x}^{2} + 1\right) \cdot x \]
      4. *-commutativeN/A

        \[\leadsto \left({x}^{2} \cdot \frac{1}{3} + 1\right) \cdot x \]
      5. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left({x}^{2}, \frac{1}{3}, 1\right) \cdot x \]
      6. unpow2N/A

        \[\leadsto \mathsf{fma}\left(x \cdot x, \frac{1}{3}, 1\right) \cdot x \]
      7. lower-*.f3298.3

        \[\leadsto \mathsf{fma}\left(x \cdot x, 0.3333333333333333, 1\right) \cdot x \]
    4. Applied rewrites98.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(x \cdot x, 0.3333333333333333, 1\right) \cdot x} \]
    5. Taylor expanded in x around inf

      \[\leadsto {x}^{3} \cdot \color{blue}{\left(\frac{1}{3} + \frac{1}{{x}^{2}}\right)} \]
    6. Step-by-step derivation
      1. distribute-lft-inN/A

        \[\leadsto {x}^{3} \cdot \frac{1}{3} + {x}^{3} \cdot \color{blue}{\frac{1}{{x}^{2}}} \]
      2. pow-flipN/A

        \[\leadsto {x}^{3} \cdot \frac{1}{3} + {x}^{3} \cdot {x}^{\left(\mathsf{neg}\left(2\right)\right)} \]
      3. metadata-evalN/A

        \[\leadsto {x}^{3} \cdot \frac{1}{3} + {x}^{3} \cdot {x}^{-2} \]
      4. pow-prod-upN/A

        \[\leadsto {x}^{3} \cdot \frac{1}{3} + {x}^{\left(3 + \color{blue}{-2}\right)} \]
      5. metadata-evalN/A

        \[\leadsto {x}^{3} \cdot \frac{1}{3} + {x}^{1} \]
      6. unpow1N/A

        \[\leadsto {x}^{3} \cdot \frac{1}{3} + x \]
      7. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left({x}^{3}, \frac{1}{3}, x\right) \]
      8. unpow3N/A

        \[\leadsto \mathsf{fma}\left(\left(x \cdot x\right) \cdot x, \frac{1}{3}, x\right) \]
      9. pow2N/A

        \[\leadsto \mathsf{fma}\left({x}^{2} \cdot x, \frac{1}{3}, x\right) \]
      10. lower-*.f32N/A

        \[\leadsto \mathsf{fma}\left({x}^{2} \cdot x, \frac{1}{3}, x\right) \]
      11. pow2N/A

        \[\leadsto \mathsf{fma}\left(\left(x \cdot x\right) \cdot x, \frac{1}{3}, x\right) \]
      12. lift-*.f3298.4

        \[\leadsto \mathsf{fma}\left(\left(x \cdot x\right) \cdot x, 0.3333333333333333, x\right) \]
    7. Applied rewrites98.4%

      \[\leadsto \mathsf{fma}\left(\left(x \cdot x\right) \cdot x, \color{blue}{0.3333333333333333}, x\right) \]
    8. Add Preprocessing

    Alternative 9: 96.7% accurate, 125.0× speedup?

    \[\begin{array}{l} \\ x \end{array} \]
    (FPCore (x) :precision binary32 x)
    float code(float x) {
    	return x;
    }
    
    module fmin_fmax_functions
        implicit none
        private
        public fmax
        public fmin
    
        interface fmax
            module procedure fmax88
            module procedure fmax44
            module procedure fmax84
            module procedure fmax48
        end interface
        interface fmin
            module procedure fmin88
            module procedure fmin44
            module procedure fmin84
            module procedure fmin48
        end interface
    contains
        real(8) function fmax88(x, y) result (res)
            real(8), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
        end function
        real(4) function fmax44(x, y) result (res)
            real(4), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
        end function
        real(8) function fmax84(x, y) result(res)
            real(8), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
        end function
        real(8) function fmax48(x, y) result(res)
            real(4), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
        end function
        real(8) function fmin88(x, y) result (res)
            real(8), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
        end function
        real(4) function fmin44(x, y) result (res)
            real(4), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
        end function
        real(8) function fmin84(x, y) result(res)
            real(8), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
        end function
        real(8) function fmin48(x, y) result(res)
            real(4), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
        end function
    end module
    
    real(4) function code(x)
    use fmin_fmax_functions
        real(4), intent (in) :: x
        code = x
    end function
    
    function code(x)
    	return x
    end
    
    function tmp = code(x)
    	tmp = x;
    end
    
    \begin{array}{l}
    
    \\
    x
    \end{array}
    
    Derivation
    1. Initial program 99.8%

      \[0.5 \cdot \mathsf{log1p}\left(\frac{2 \cdot x}{1 - x}\right) \]
    2. Taylor expanded in x around 0

      \[\leadsto \color{blue}{x} \]
    3. Step-by-step derivation
      1. Applied rewrites96.7%

        \[\leadsto \color{blue}{x} \]
      2. Add Preprocessing

      Reproduce

      ?
      herbie shell --seed 2025101 
      (FPCore (x)
        :name "Rust f32::atanh"
        :precision binary32
        (* 0.5 (log1p (/ (* 2.0 x) (- 1.0 x)))))