2cbrt (problem 3.3.4)

Percentage Accurate: 6.8% → 97.6%
Time: 2.7s
Alternatives: 7
Speedup: 1.4×

Specification

?
\[x > 1 \land x < 10^{+308}\]
\[\begin{array}{l} \\ \sqrt[3]{x + 1} - \sqrt[3]{x} \end{array} \]
(FPCore (x) :precision binary64 (- (cbrt (+ x 1.0)) (cbrt x)))
double code(double x) {
	return cbrt((x + 1.0)) - cbrt(x);
}
public static double code(double x) {
	return Math.cbrt((x + 1.0)) - Math.cbrt(x);
}
function code(x)
	return Float64(cbrt(Float64(x + 1.0)) - cbrt(x))
end
code[x_] := N[(N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\sqrt[3]{x + 1} - \sqrt[3]{x}
\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 7 alternatives:

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

Initial Program: 6.8% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt[3]{x + 1} - \sqrt[3]{x} \end{array} \]
(FPCore (x) :precision binary64 (- (cbrt (+ x 1.0)) (cbrt x)))
double code(double x) {
	return cbrt((x + 1.0)) - cbrt(x);
}
public static double code(double x) {
	return Math.cbrt((x + 1.0)) - Math.cbrt(x);
}
function code(x)
	return Float64(cbrt(Float64(x + 1.0)) - cbrt(x))
end
code[x_] := N[(N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\sqrt[3]{x + 1} - \sqrt[3]{x}
\end{array}

Alternative 1: 97.6% accurate, 0.4× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \sqrt[3]{{x}^{-1}}\right) \cdot 0.3333333333333333\right) \end{array} \]
(FPCore (x)
 :precision binary64
 (fma
  (pow x -1.6666666666666667)
  -0.1111111111111111
  (* (* (pow (cbrt x) -1.0) (cbrt (pow x -1.0))) 0.3333333333333333)))
double code(double x) {
	return fma(pow(x, -1.6666666666666667), -0.1111111111111111, ((pow(cbrt(x), -1.0) * cbrt(pow(x, -1.0))) * 0.3333333333333333));
}
function code(x)
	return fma((x ^ -1.6666666666666667), -0.1111111111111111, Float64(Float64((cbrt(x) ^ -1.0) * cbrt((x ^ -1.0))) * 0.3333333333333333))
end
code[x_] := N[(N[Power[x, -1.6666666666666667], $MachinePrecision] * -0.1111111111111111 + N[(N[(N[Power[N[Power[x, 1/3], $MachinePrecision], -1.0], $MachinePrecision] * N[Power[N[Power[x, -1.0], $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision] * 0.3333333333333333), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \sqrt[3]{{x}^{-1}}\right) \cdot 0.3333333333333333\right)
\end{array}
Derivation
  1. Initial program 6.8%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{\frac{-1}{9} \cdot \sqrt[3]{x} + \frac{1}{3} \cdot \sqrt[3]{{x}^{4}}}{{x}^{2}}} \]
  3. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \frac{\frac{-1}{9} \cdot \sqrt[3]{x} + \frac{1}{3} \cdot \sqrt[3]{{x}^{4}}}{\color{blue}{{x}^{2}}} \]
    2. +-commutativeN/A

      \[\leadsto \frac{\frac{1}{3} \cdot \sqrt[3]{{x}^{4}} + \frac{-1}{9} \cdot \sqrt[3]{x}}{{\color{blue}{x}}^{2}} \]
    3. *-commutativeN/A

      \[\leadsto \frac{\sqrt[3]{{x}^{4}} \cdot \frac{1}{3} + \frac{-1}{9} \cdot \sqrt[3]{x}}{{x}^{2}} \]
    4. lower-fma.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left(\sqrt[3]{{x}^{4}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{\color{blue}{x}}^{2}} \]
    5. pow1/3N/A

      \[\leadsto \frac{\mathsf{fma}\left({\left({x}^{4}\right)}^{\frac{1}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    6. pow-powN/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\left(4 \cdot \frac{1}{3}\right)}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    7. lower-pow.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\left(4 \cdot \frac{1}{3}\right)}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    8. metadata-evalN/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    9. lower-*.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    10. lift-cbrt.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    11. unpow2N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{x \cdot \color{blue}{x}} \]
    12. lower-*.f6445.2

      \[\leadsto \frac{\mathsf{fma}\left({x}^{1.3333333333333333}, 0.3333333333333333, -0.1111111111111111 \cdot \sqrt[3]{x}\right)}{x \cdot \color{blue}{x}} \]
  4. Applied rewrites45.2%

    \[\leadsto \color{blue}{\frac{\mathsf{fma}\left({x}^{1.3333333333333333}, 0.3333333333333333, -0.1111111111111111 \cdot \sqrt[3]{x}\right)}{x \cdot x}} \]
  5. Taylor expanded in x around inf

    \[\leadsto \frac{-1}{9} \cdot \sqrt[3]{\frac{1}{{x}^{5}}} + \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  6. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{5}}} \cdot \frac{-1}{9} + \frac{1}{3} \cdot \sqrt[3]{\color{blue}{\frac{1}{{x}^{2}}}} \]
    2. lower-fma.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{1}{{x}^{5}}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    3. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({\left(\frac{1}{{x}^{5}}\right)}^{\frac{1}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    4. pow-flipN/A

      \[\leadsto \mathsf{fma}\left({\left({x}^{\left(\mathsf{neg}\left(5\right)\right)}\right)}^{\frac{1}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    5. pow-powN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\left(\mathsf{neg}\left(5\right)\right) \cdot \frac{1}{3}\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    6. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(-5 \cdot \frac{1}{3}\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    7. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    8. metadata-evalN/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(5\right)\right)\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    10. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(5\right)\right)\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    11. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot -5\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    12. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    13. pow1/3N/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}}\right) \]
    15. pow-powN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {x}^{\left(\left(\mathsf{neg}\left(2\right)\right) \cdot \frac{1}{3}\right)}\right) \]
    16. metadata-evalN/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {x}^{\frac{-2}{3}}\right) \]
    18. lift-pow.f64N/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {x}^{\frac{-2}{3}} \cdot \frac{1}{3}\right) \]
    20. lift-*.f6489.9

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {x}^{-0.6666666666666666} \cdot 0.3333333333333333\right) \]
  7. Applied rewrites89.9%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, \color{blue}{-0.1111111111111111}, {x}^{-0.6666666666666666} \cdot 0.3333333333333333\right) \]
  8. Step-by-step derivation
    1. lift-pow.f64N/A

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

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

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({x}^{\left(\frac{1}{3} + \frac{1}{3}\right)}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    5. pow-prod-upN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({x}^{\frac{1}{3}} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    6. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left(\sqrt[3]{x} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    7. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left(\sqrt[3]{x} \cdot \sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    8. unpow-prod-downN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    9. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    10. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    11. lift-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    12. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    13. lift-cbrt.f6497.5

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot 0.3333333333333333\right) \]
  9. Applied rewrites97.5%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot 0.3333333333333333\right) \]
  10. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    2. lift-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    3. unpow-1N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{\sqrt[3]{x}}\right) \cdot \frac{1}{3}\right) \]
    4. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \frac{\sqrt[3]{1}}{\sqrt[3]{x}}\right) \cdot \frac{1}{3}\right) \]
    5. cbrt-divN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \sqrt[3]{\frac{1}{x}}\right) \cdot \frac{1}{3}\right) \]
    6. inv-powN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \sqrt[3]{{x}^{-1}}\right) \cdot \frac{1}{3}\right) \]
    7. lift-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \sqrt[3]{{x}^{-1}}\right) \cdot \frac{1}{3}\right) \]
    8. lift-cbrt.f6497.6

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \sqrt[3]{{x}^{-1}}\right) \cdot 0.3333333333333333\right) \]
  11. Applied rewrites97.6%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot \sqrt[3]{{x}^{-1}}\right) \cdot 0.3333333333333333\right) \]
  12. Add Preprocessing

Alternative 2: 97.6% accurate, 0.5× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot 0.3333333333333333\right) \end{array} \]
(FPCore (x)
 :precision binary64
 (fma
  (pow x -1.6666666666666667)
  -0.1111111111111111
  (* (pow (pow (cbrt x) 2.0) -1.0) 0.3333333333333333)))
double code(double x) {
	return fma(pow(x, -1.6666666666666667), -0.1111111111111111, (pow(pow(cbrt(x), 2.0), -1.0) * 0.3333333333333333));
}
function code(x)
	return fma((x ^ -1.6666666666666667), -0.1111111111111111, Float64(((cbrt(x) ^ 2.0) ^ -1.0) * 0.3333333333333333))
end
code[x_] := N[(N[Power[x, -1.6666666666666667], $MachinePrecision] * -0.1111111111111111 + N[(N[Power[N[Power[N[Power[x, 1/3], $MachinePrecision], 2.0], $MachinePrecision], -1.0], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot 0.3333333333333333\right)
\end{array}
Derivation
  1. Initial program 6.8%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{\frac{-1}{9} \cdot \sqrt[3]{x} + \frac{1}{3} \cdot \sqrt[3]{{x}^{4}}}{{x}^{2}}} \]
  3. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \frac{\frac{-1}{9} \cdot \sqrt[3]{x} + \frac{1}{3} \cdot \sqrt[3]{{x}^{4}}}{\color{blue}{{x}^{2}}} \]
    2. +-commutativeN/A

      \[\leadsto \frac{\frac{1}{3} \cdot \sqrt[3]{{x}^{4}} + \frac{-1}{9} \cdot \sqrt[3]{x}}{{\color{blue}{x}}^{2}} \]
    3. *-commutativeN/A

      \[\leadsto \frac{\sqrt[3]{{x}^{4}} \cdot \frac{1}{3} + \frac{-1}{9} \cdot \sqrt[3]{x}}{{x}^{2}} \]
    4. lower-fma.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left(\sqrt[3]{{x}^{4}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{\color{blue}{x}}^{2}} \]
    5. pow1/3N/A

      \[\leadsto \frac{\mathsf{fma}\left({\left({x}^{4}\right)}^{\frac{1}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    6. pow-powN/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\left(4 \cdot \frac{1}{3}\right)}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    7. lower-pow.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\left(4 \cdot \frac{1}{3}\right)}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    8. metadata-evalN/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    9. lower-*.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    10. lift-cbrt.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    11. unpow2N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{x \cdot \color{blue}{x}} \]
    12. lower-*.f6445.2

      \[\leadsto \frac{\mathsf{fma}\left({x}^{1.3333333333333333}, 0.3333333333333333, -0.1111111111111111 \cdot \sqrt[3]{x}\right)}{x \cdot \color{blue}{x}} \]
  4. Applied rewrites45.2%

    \[\leadsto \color{blue}{\frac{\mathsf{fma}\left({x}^{1.3333333333333333}, 0.3333333333333333, -0.1111111111111111 \cdot \sqrt[3]{x}\right)}{x \cdot x}} \]
  5. Taylor expanded in x around inf

    \[\leadsto \frac{-1}{9} \cdot \sqrt[3]{\frac{1}{{x}^{5}}} + \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  6. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{5}}} \cdot \frac{-1}{9} + \frac{1}{3} \cdot \sqrt[3]{\color{blue}{\frac{1}{{x}^{2}}}} \]
    2. lower-fma.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{1}{{x}^{5}}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    3. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({\left(\frac{1}{{x}^{5}}\right)}^{\frac{1}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    4. pow-flipN/A

      \[\leadsto \mathsf{fma}\left({\left({x}^{\left(\mathsf{neg}\left(5\right)\right)}\right)}^{\frac{1}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    5. pow-powN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\left(\mathsf{neg}\left(5\right)\right) \cdot \frac{1}{3}\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    6. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(-5 \cdot \frac{1}{3}\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    7. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    8. metadata-evalN/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(5\right)\right)\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    10. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(5\right)\right)\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    11. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot -5\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    12. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    13. pow1/3N/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}}\right) \]
    15. pow-powN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {x}^{\left(\left(\mathsf{neg}\left(2\right)\right) \cdot \frac{1}{3}\right)}\right) \]
    16. metadata-evalN/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {x}^{\frac{-2}{3}}\right) \]
    18. lift-pow.f64N/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {x}^{\frac{-2}{3}} \cdot \frac{1}{3}\right) \]
    20. lift-*.f6489.9

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {x}^{-0.6666666666666666} \cdot 0.3333333333333333\right) \]
  7. Applied rewrites89.9%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, \color{blue}{-0.1111111111111111}, {x}^{-0.6666666666666666} \cdot 0.3333333333333333\right) \]
  8. Step-by-step derivation
    1. lift-pow.f64N/A

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

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

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({x}^{\left(\frac{1}{3} + \frac{1}{3}\right)}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    5. pow-prod-upN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({x}^{\frac{1}{3}} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    6. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left(\sqrt[3]{x} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    7. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left(\sqrt[3]{x} \cdot \sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    8. unpow-prod-downN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    9. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    10. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    11. lift-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    12. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    13. lift-cbrt.f6497.5

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot 0.3333333333333333\right) \]
  9. Applied rewrites97.5%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot 0.3333333333333333\right) \]
  10. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    2. lift-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    3. lift-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    4. lift-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    5. lift-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    6. pow-prod-downN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left(\sqrt[3]{x} \cdot \sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    7. unpow2N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    8. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    9. lift-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    10. lift-cbrt.f6497.6

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot 0.3333333333333333\right) \]
  11. Applied rewrites97.6%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot 0.3333333333333333\right) \]
  12. Add Preprocessing

Alternative 3: 97.5% accurate, 0.5× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {\left({\left(\sqrt[3]{x}\right)}^{-1}\right)}^{2} \cdot 0.3333333333333333\right) \end{array} \]
(FPCore (x)
 :precision binary64
 (fma
  (pow x -1.6666666666666667)
  -0.1111111111111111
  (* (pow (pow (cbrt x) -1.0) 2.0) 0.3333333333333333)))
double code(double x) {
	return fma(pow(x, -1.6666666666666667), -0.1111111111111111, (pow(pow(cbrt(x), -1.0), 2.0) * 0.3333333333333333));
}
function code(x)
	return fma((x ^ -1.6666666666666667), -0.1111111111111111, Float64(((cbrt(x) ^ -1.0) ^ 2.0) * 0.3333333333333333))
end
code[x_] := N[(N[Power[x, -1.6666666666666667], $MachinePrecision] * -0.1111111111111111 + N[(N[Power[N[Power[N[Power[x, 1/3], $MachinePrecision], -1.0], $MachinePrecision], 2.0], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {\left({\left(\sqrt[3]{x}\right)}^{-1}\right)}^{2} \cdot 0.3333333333333333\right)
\end{array}
Derivation
  1. Initial program 6.8%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{\frac{-1}{9} \cdot \sqrt[3]{x} + \frac{1}{3} \cdot \sqrt[3]{{x}^{4}}}{{x}^{2}}} \]
  3. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \frac{\frac{-1}{9} \cdot \sqrt[3]{x} + \frac{1}{3} \cdot \sqrt[3]{{x}^{4}}}{\color{blue}{{x}^{2}}} \]
    2. +-commutativeN/A

      \[\leadsto \frac{\frac{1}{3} \cdot \sqrt[3]{{x}^{4}} + \frac{-1}{9} \cdot \sqrt[3]{x}}{{\color{blue}{x}}^{2}} \]
    3. *-commutativeN/A

      \[\leadsto \frac{\sqrt[3]{{x}^{4}} \cdot \frac{1}{3} + \frac{-1}{9} \cdot \sqrt[3]{x}}{{x}^{2}} \]
    4. lower-fma.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left(\sqrt[3]{{x}^{4}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{\color{blue}{x}}^{2}} \]
    5. pow1/3N/A

      \[\leadsto \frac{\mathsf{fma}\left({\left({x}^{4}\right)}^{\frac{1}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    6. pow-powN/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\left(4 \cdot \frac{1}{3}\right)}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    7. lower-pow.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\left(4 \cdot \frac{1}{3}\right)}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    8. metadata-evalN/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    9. lower-*.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    10. lift-cbrt.f64N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{{x}^{2}} \]
    11. unpow2N/A

      \[\leadsto \frac{\mathsf{fma}\left({x}^{\frac{4}{3}}, \frac{1}{3}, \frac{-1}{9} \cdot \sqrt[3]{x}\right)}{x \cdot \color{blue}{x}} \]
    12. lower-*.f6445.2

      \[\leadsto \frac{\mathsf{fma}\left({x}^{1.3333333333333333}, 0.3333333333333333, -0.1111111111111111 \cdot \sqrt[3]{x}\right)}{x \cdot \color{blue}{x}} \]
  4. Applied rewrites45.2%

    \[\leadsto \color{blue}{\frac{\mathsf{fma}\left({x}^{1.3333333333333333}, 0.3333333333333333, -0.1111111111111111 \cdot \sqrt[3]{x}\right)}{x \cdot x}} \]
  5. Taylor expanded in x around inf

    \[\leadsto \frac{-1}{9} \cdot \sqrt[3]{\frac{1}{{x}^{5}}} + \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  6. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{5}}} \cdot \frac{-1}{9} + \frac{1}{3} \cdot \sqrt[3]{\color{blue}{\frac{1}{{x}^{2}}}} \]
    2. lower-fma.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt[3]{\frac{1}{{x}^{5}}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    3. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({\left(\frac{1}{{x}^{5}}\right)}^{\frac{1}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    4. pow-flipN/A

      \[\leadsto \mathsf{fma}\left({\left({x}^{\left(\mathsf{neg}\left(5\right)\right)}\right)}^{\frac{1}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    5. pow-powN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\left(\mathsf{neg}\left(5\right)\right) \cdot \frac{1}{3}\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    6. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(-5 \cdot \frac{1}{3}\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    7. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    8. metadata-evalN/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(5\right)\right)\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    10. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(5\right)\right)\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    11. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\left(\frac{1}{3} \cdot -5\right)}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    12. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\right) \]
    13. pow1/3N/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}}\right) \]
    15. pow-powN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {x}^{\left(\left(\mathsf{neg}\left(2\right)\right) \cdot \frac{1}{3}\right)}\right) \]
    16. metadata-evalN/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \frac{1}{3} \cdot {x}^{\frac{-2}{3}}\right) \]
    18. lift-pow.f64N/A

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {x}^{\frac{-2}{3}} \cdot \frac{1}{3}\right) \]
    20. lift-*.f6489.9

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {x}^{-0.6666666666666666} \cdot 0.3333333333333333\right) \]
  7. Applied rewrites89.9%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, \color{blue}{-0.1111111111111111}, {x}^{-0.6666666666666666} \cdot 0.3333333333333333\right) \]
  8. Step-by-step derivation
    1. lift-pow.f64N/A

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

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

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

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({x}^{\left(\frac{1}{3} + \frac{1}{3}\right)}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    5. pow-prod-upN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({x}^{\frac{1}{3}} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    6. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left(\sqrt[3]{x} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    7. pow1/3N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left(\sqrt[3]{x} \cdot \sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{3}\right) \]
    8. unpow-prod-downN/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    9. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    10. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    11. lift-cbrt.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    12. lower-pow.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    13. lift-cbrt.f6497.5

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot 0.3333333333333333\right) \]
  9. Applied rewrites97.5%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot 0.3333333333333333\right) \]
  10. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, \left({\left(\sqrt[3]{x}\right)}^{-1} \cdot {\left(\sqrt[3]{x}\right)}^{-1}\right) \cdot \frac{1}{3}\right) \]
    2. pow2N/A

      \[\leadsto \mathsf{fma}\left({x}^{\frac{-5}{3}}, \frac{-1}{9}, {\left({\left(\sqrt[3]{x}\right)}^{-1}\right)}^{2} \cdot \frac{1}{3}\right) \]
    3. lower-pow.f6497.5

      \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {\left({\left(\sqrt[3]{x}\right)}^{-1}\right)}^{2} \cdot 0.3333333333333333\right) \]
  11. Applied rewrites97.5%

    \[\leadsto \mathsf{fma}\left({x}^{-1.6666666666666667}, -0.1111111111111111, {\left({\left(\sqrt[3]{x}\right)}^{-1}\right)}^{2} \cdot 0.3333333333333333\right) \]
  12. Add Preprocessing

Alternative 4: 96.6% accurate, 1.2× speedup?

\[\begin{array}{l} \\ {\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333 \end{array} \]
(FPCore (x) :precision binary64 (* (pow (cbrt x) -2.0) 0.3333333333333333))
double code(double x) {
	return pow(cbrt(x), -2.0) * 0.3333333333333333;
}
public static double code(double x) {
	return Math.pow(Math.cbrt(x), -2.0) * 0.3333333333333333;
}
function code(x)
	return Float64((cbrt(x) ^ -2.0) * 0.3333333333333333)
end
code[x_] := N[(N[Power[N[Power[x, 1/3], $MachinePrecision], -2.0], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]
\begin{array}{l}

\\
{\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333
\end{array}
Derivation
  1. Initial program 6.8%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Taylor expanded in x around inf

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

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. pow1/3N/A

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

      \[\leadsto {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    5. pow-powN/A

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

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

      \[\leadsto {x}^{\frac{-2}{3}} \cdot \frac{1}{3} \]
    8. metadata-evalN/A

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

      \[\leadsto {x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(2\right)\right)\right)} \cdot \frac{1}{3} \]
    10. lower-pow.f64N/A

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

      \[\leadsto {x}^{\left(\frac{1}{3} \cdot -2\right)} \cdot \frac{1}{3} \]
    12. metadata-eval89.0

      \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
  4. Applied rewrites89.0%

    \[\leadsto \color{blue}{{x}^{-0.6666666666666666} \cdot 0.3333333333333333} \]
  5. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto {x}^{\frac{-2}{3}} \cdot \frac{1}{3} \]
    2. metadata-evalN/A

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

      \[\leadsto {x}^{\left(\left(\mathsf{neg}\left(2\right)\right) \cdot \frac{1}{3}\right)} \cdot \frac{1}{3} \]
    4. pow-powN/A

      \[\leadsto {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    5. pow-flipN/A

      \[\leadsto {\left(\frac{1}{{x}^{2}}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    6. pow1/3N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    7. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    8. metadata-evalN/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    9. inv-powN/A

      \[\leadsto {\left(\sqrt[3]{{x}^{2}}\right)}^{-1} \cdot \frac{1}{3} \]
    10. pow2N/A

      \[\leadsto {\left(\sqrt[3]{x \cdot x}\right)}^{-1} \cdot \frac{1}{3} \]
    11. cbrt-prodN/A

      \[\leadsto {\left(\sqrt[3]{x} \cdot \sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{3} \]
    12. lower-pow.f64N/A

      \[\leadsto {\left(\sqrt[3]{x} \cdot \sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{3} \]
    13. pow1/3N/A

      \[\leadsto {\left({x}^{\frac{1}{3}} \cdot \sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{3} \]
    14. pow1/3N/A

      \[\leadsto {\left({x}^{\frac{1}{3}} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3} \]
    15. pow-prod-upN/A

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

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

      \[\leadsto {\left({x}^{\left(\frac{\frac{4}{3}}{2}\right)}\right)}^{-1} \cdot \frac{1}{3} \]
    18. lower-pow.f64N/A

      \[\leadsto {\left({x}^{\left(\frac{\frac{4}{3}}{2}\right)}\right)}^{-1} \cdot \frac{1}{3} \]
    19. metadata-eval89.0

      \[\leadsto {\left({x}^{0.6666666666666666}\right)}^{-1} \cdot 0.3333333333333333 \]
  6. Applied rewrites89.0%

    \[\leadsto {\left({x}^{0.6666666666666666}\right)}^{-1} \cdot 0.3333333333333333 \]
  7. Step-by-step derivation
    1. lift-pow.f64N/A

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

      \[\leadsto {\left({x}^{\left(\frac{1}{3} + \frac{1}{3}\right)}\right)}^{-1} \cdot \frac{1}{3} \]
    3. pow-prod-upN/A

      \[\leadsto {\left({x}^{\frac{1}{3}} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3} \]
    4. pow1/3N/A

      \[\leadsto {\left(\sqrt[3]{x} \cdot {x}^{\frac{1}{3}}\right)}^{-1} \cdot \frac{1}{3} \]
    5. pow1/3N/A

      \[\leadsto {\left(\sqrt[3]{x} \cdot \sqrt[3]{x}\right)}^{-1} \cdot \frac{1}{3} \]
    6. pow2N/A

      \[\leadsto {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot \frac{1}{3} \]
    7. lower-pow.f64N/A

      \[\leadsto {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot \frac{1}{3} \]
    8. lift-cbrt.f6496.6

      \[\leadsto {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot 0.3333333333333333 \]
  8. Applied rewrites96.6%

    \[\leadsto {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot 0.3333333333333333 \]
  9. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot \frac{1}{3} \]
    2. lift-cbrt.f64N/A

      \[\leadsto {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto {\left({\left(\sqrt[3]{x}\right)}^{2}\right)}^{-1} \cdot \frac{1}{3} \]
    4. pow-powN/A

      \[\leadsto {\left(\sqrt[3]{x}\right)}^{\left(2 \cdot -1\right)} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto {\left(\sqrt[3]{x}\right)}^{\left(2 \cdot -1\right)} \cdot \frac{1}{3} \]
    6. lift-cbrt.f64N/A

      \[\leadsto {\left(\sqrt[3]{x}\right)}^{\left(2 \cdot -1\right)} \cdot \frac{1}{3} \]
    7. metadata-eval96.6

      \[\leadsto {\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333 \]
  10. Applied rewrites96.6%

    \[\leadsto \color{blue}{{\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333} \]
  11. Add Preprocessing

Alternative 5: 92.1% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 2.1 \cdot 10^{+155}:\\ \;\;\;\;\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333\\ \mathbf{else}:\\ \;\;\;\;{x}^{-0.6666666666666666} \cdot 0.3333333333333333\\ \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (if (<= x 2.1e+155)
   (* (cbrt (pow x -2.0)) 0.3333333333333333)
   (* (pow x -0.6666666666666666) 0.3333333333333333)))
double code(double x) {
	double tmp;
	if (x <= 2.1e+155) {
		tmp = cbrt(pow(x, -2.0)) * 0.3333333333333333;
	} else {
		tmp = pow(x, -0.6666666666666666) * 0.3333333333333333;
	}
	return tmp;
}
public static double code(double x) {
	double tmp;
	if (x <= 2.1e+155) {
		tmp = Math.cbrt(Math.pow(x, -2.0)) * 0.3333333333333333;
	} else {
		tmp = Math.pow(x, -0.6666666666666666) * 0.3333333333333333;
	}
	return tmp;
}
function code(x)
	tmp = 0.0
	if (x <= 2.1e+155)
		tmp = Float64(cbrt((x ^ -2.0)) * 0.3333333333333333);
	else
		tmp = Float64((x ^ -0.6666666666666666) * 0.3333333333333333);
	end
	return tmp
end
code[x_] := If[LessEqual[x, 2.1e+155], N[(N[Power[N[Power[x, -2.0], $MachinePrecision], 1/3], $MachinePrecision] * 0.3333333333333333), $MachinePrecision], N[(N[Power[x, -0.6666666666666666], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 2.1 \cdot 10^{+155}:\\
\;\;\;\;\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333\\

\mathbf{else}:\\
\;\;\;\;{x}^{-0.6666666666666666} \cdot 0.3333333333333333\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < 2.1e155

    1. Initial program 8.8%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
    2. Taylor expanded in x around inf

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

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      2. lower-*.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      3. pow1/3N/A

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

        \[\leadsto {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      5. pow-powN/A

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

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

        \[\leadsto {x}^{\frac{-2}{3}} \cdot \frac{1}{3} \]
      8. metadata-evalN/A

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

        \[\leadsto {x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(2\right)\right)\right)} \cdot \frac{1}{3} \]
      10. lower-pow.f64N/A

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

        \[\leadsto {x}^{\left(\frac{1}{3} \cdot -2\right)} \cdot \frac{1}{3} \]
      12. metadata-eval88.8

        \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
    4. Applied rewrites88.8%

      \[\leadsto \color{blue}{{x}^{-0.6666666666666666} \cdot 0.3333333333333333} \]
    5. Step-by-step derivation
      1. lift-pow.f64N/A

        \[\leadsto {x}^{\frac{-2}{3}} \cdot \frac{1}{3} \]
      2. metadata-evalN/A

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

        \[\leadsto {x}^{\left(\left(\mathsf{neg}\left(2\right)\right) \cdot \frac{1}{3}\right)} \cdot \frac{1}{3} \]
      4. pow-powN/A

        \[\leadsto {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      5. pow-flipN/A

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

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

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

        \[\leadsto {\left(\frac{1}{x} \cdot \frac{1}{x}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      9. pow1/3N/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      10. lower-cbrt.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      11. frac-timesN/A

        \[\leadsto \sqrt[3]{\frac{1 \cdot 1}{x \cdot x}} \cdot \frac{1}{3} \]
      12. metadata-evalN/A

        \[\leadsto \sqrt[3]{\frac{1}{x \cdot x}} \cdot \frac{1}{3} \]
      13. pow2N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
      14. pow-flipN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      15. lower-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      16. metadata-eval95.1

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
    6. Applied rewrites95.1%

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]

    if 2.1e155 < x

    1. Initial program 4.7%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
    2. Taylor expanded in x around inf

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

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      2. lower-*.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      3. pow1/3N/A

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

        \[\leadsto {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      5. pow-powN/A

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

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

        \[\leadsto {x}^{\frac{-2}{3}} \cdot \frac{1}{3} \]
      8. metadata-evalN/A

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

        \[\leadsto {x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(2\right)\right)\right)} \cdot \frac{1}{3} \]
      10. lower-pow.f64N/A

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

        \[\leadsto {x}^{\left(\frac{1}{3} \cdot -2\right)} \cdot \frac{1}{3} \]
      12. metadata-eval89.1

        \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
    4. Applied rewrites89.1%

      \[\leadsto \color{blue}{{x}^{-0.6666666666666666} \cdot 0.3333333333333333} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 6: 89.0% accurate, 1.4× speedup?

\[\begin{array}{l} \\ {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \end{array} \]
(FPCore (x)
 :precision binary64
 (* (pow x -0.6666666666666666) 0.3333333333333333))
double code(double x) {
	return pow(x, -0.6666666666666666) * 0.3333333333333333;
}
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(8) function code(x)
use fmin_fmax_functions
    real(8), intent (in) :: x
    code = (x ** (-0.6666666666666666d0)) * 0.3333333333333333d0
end function
public static double code(double x) {
	return Math.pow(x, -0.6666666666666666) * 0.3333333333333333;
}
def code(x):
	return math.pow(x, -0.6666666666666666) * 0.3333333333333333
function code(x)
	return Float64((x ^ -0.6666666666666666) * 0.3333333333333333)
end
function tmp = code(x)
	tmp = (x ^ -0.6666666666666666) * 0.3333333333333333;
end
code[x_] := N[(N[Power[x, -0.6666666666666666], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]
\begin{array}{l}

\\
{x}^{-0.6666666666666666} \cdot 0.3333333333333333
\end{array}
Derivation
  1. Initial program 6.8%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Taylor expanded in x around inf

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

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. pow1/3N/A

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

      \[\leadsto {\left({x}^{\left(\mathsf{neg}\left(2\right)\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    5. pow-powN/A

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

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

      \[\leadsto {x}^{\frac{-2}{3}} \cdot \frac{1}{3} \]
    8. metadata-evalN/A

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

      \[\leadsto {x}^{\left(\frac{1}{3} \cdot \left(\mathsf{neg}\left(2\right)\right)\right)} \cdot \frac{1}{3} \]
    10. lower-pow.f64N/A

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

      \[\leadsto {x}^{\left(\frac{1}{3} \cdot -2\right)} \cdot \frac{1}{3} \]
    12. metadata-eval89.0

      \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
  4. Applied rewrites89.0%

    \[\leadsto \color{blue}{{x}^{-0.6666666666666666} \cdot 0.3333333333333333} \]
  5. Add Preprocessing

Alternative 7: 1.8% accurate, 1.8× speedup?

\[\begin{array}{l} \\ 1 - \sqrt[3]{x} \end{array} \]
(FPCore (x) :precision binary64 (- 1.0 (cbrt x)))
double code(double x) {
	return 1.0 - cbrt(x);
}
public static double code(double x) {
	return 1.0 - Math.cbrt(x);
}
function code(x)
	return Float64(1.0 - cbrt(x))
end
code[x_] := N[(1.0 - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
1 - \sqrt[3]{x}
\end{array}
Derivation
  1. Initial program 6.8%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Taylor expanded in x around 0

    \[\leadsto \color{blue}{1} - \sqrt[3]{x} \]
  3. Step-by-step derivation
    1. Applied rewrites1.8%

      \[\leadsto \color{blue}{1} - \sqrt[3]{x} \]
    2. Add Preprocessing

    Reproduce

    ?
    herbie shell --seed 2025101 
    (FPCore (x)
      :name "2cbrt (problem 3.3.4)"
      :precision binary64
      :pre (and (> x 1.0) (< x 1e+308))
      (- (cbrt (+ x 1.0)) (cbrt x)))