
(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}
Sampling outcomes in binary64 precision:
Herbie found 11 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(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}
(FPCore (x) :precision binary64 (/ 1.0 (+ (+ (pow (cbrt (+ 1.0 x)) 2.0) (pow (cbrt x) 2.0)) (* x (cbrt (+ (/ 1.0 (pow x 2.0)) (/ 1.0 x)))))))
double code(double x) {
return 1.0 / ((pow(cbrt((1.0 + x)), 2.0) + pow(cbrt(x), 2.0)) + (x * cbrt(((1.0 / pow(x, 2.0)) + (1.0 / x)))));
}
public static double code(double x) {
return 1.0 / ((Math.pow(Math.cbrt((1.0 + x)), 2.0) + Math.pow(Math.cbrt(x), 2.0)) + (x * Math.cbrt(((1.0 / Math.pow(x, 2.0)) + (1.0 / x)))));
}
function code(x) return Float64(1.0 / Float64(Float64((cbrt(Float64(1.0 + x)) ^ 2.0) + (cbrt(x) ^ 2.0)) + Float64(x * cbrt(Float64(Float64(1.0 / (x ^ 2.0)) + Float64(1.0 / x)))))) end
code[x_] := N[(1.0 / N[(N[(N[Power[N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Power[x, 1/3], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(x * N[Power[N[(N[(1.0 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\left({\left(\sqrt[3]{1 + x}\right)}^{2} + {\left(\sqrt[3]{x}\right)}^{2}\right) + x \cdot \sqrt[3]{\frac{1}{{x}^{2}} + \frac{1}{x}}}
\end{array}
Initial program 7.7%
flip3--8.1%
div-inv8.1%
rem-cube-cbrt8.2%
rem-cube-cbrt11.3%
+-commutative11.3%
distribute-rgt-out11.2%
+-commutative11.2%
fma-define11.2%
add-exp-log11.2%
Applied egg-rr11.2%
associate-*r/11.2%
*-rgt-identity11.2%
+-commutative11.2%
associate--l+93.3%
+-inverses93.3%
metadata-eval93.3%
+-commutative93.3%
exp-prod92.6%
Simplified92.6%
pow-exp93.3%
*-commutative93.3%
log1p-undefine93.3%
+-commutative93.3%
exp-to-pow93.1%
metadata-eval93.1%
pow-sqr93.1%
pow1/394.5%
pow1/398.5%
cbrt-unprod52.9%
pow252.9%
Applied egg-rr52.9%
fma-undefine52.9%
+-commutative52.9%
pow1/351.4%
add-exp-log51.7%
log1p-undefine51.7%
exp-prod51.4%
distribute-rgt-in51.4%
+-commutative51.4%
associate-+r+51.4%
unpow251.4%
cbrt-unprod94.6%
pow294.6%
pow294.6%
Applied egg-rr52.9%
Taylor expanded in x around inf 98.8%
+-commutative98.8%
Simplified98.8%
Final simplification98.8%
(FPCore (x) :precision binary64 (let* ((t_0 (cbrt (+ 1.0 x)))) (/ 1.0 (fma (cbrt x) (+ t_0 (cbrt x)) (pow t_0 2.0)))))
double code(double x) {
double t_0 = cbrt((1.0 + x));
return 1.0 / fma(cbrt(x), (t_0 + cbrt(x)), pow(t_0, 2.0));
}
function code(x) t_0 = cbrt(Float64(1.0 + x)) return Float64(1.0 / fma(cbrt(x), Float64(t_0 + cbrt(x)), (t_0 ^ 2.0))) end
code[x_] := Block[{t$95$0 = N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision]}, N[(1.0 / N[(N[Power[x, 1/3], $MachinePrecision] * N[(t$95$0 + N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt[3]{1 + x}\\
\frac{1}{\mathsf{fma}\left(\sqrt[3]{x}, t\_0 + \sqrt[3]{x}, {t\_0}^{2}\right)}
\end{array}
\end{array}
Initial program 7.7%
flip3--8.1%
div-inv8.1%
rem-cube-cbrt8.2%
rem-cube-cbrt11.3%
+-commutative11.3%
distribute-rgt-out11.2%
+-commutative11.2%
fma-define11.2%
add-exp-log11.2%
Applied egg-rr11.2%
associate-*r/11.2%
*-rgt-identity11.2%
+-commutative11.2%
associate--l+93.3%
+-inverses93.3%
metadata-eval93.3%
+-commutative93.3%
exp-prod92.6%
Simplified92.6%
pow-exp93.3%
*-commutative93.3%
log1p-undefine93.3%
+-commutative93.3%
exp-to-pow93.1%
metadata-eval93.1%
pow-sqr93.1%
pow1/394.5%
pow1/398.5%
Applied egg-rr98.5%
pow298.5%
Applied egg-rr98.5%
Final simplification98.5%
(FPCore (x) :precision binary64 (let* ((t_0 (cbrt (+ 1.0 x)))) (/ 1.0 (+ (pow t_0 2.0) (* (cbrt x) (+ t_0 (cbrt x)))))))
double code(double x) {
double t_0 = cbrt((1.0 + x));
return 1.0 / (pow(t_0, 2.0) + (cbrt(x) * (t_0 + cbrt(x))));
}
public static double code(double x) {
double t_0 = Math.cbrt((1.0 + x));
return 1.0 / (Math.pow(t_0, 2.0) + (Math.cbrt(x) * (t_0 + Math.cbrt(x))));
}
function code(x) t_0 = cbrt(Float64(1.0 + x)) return Float64(1.0 / Float64((t_0 ^ 2.0) + Float64(cbrt(x) * Float64(t_0 + cbrt(x))))) end
code[x_] := Block[{t$95$0 = N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision]}, N[(1.0 / N[(N[Power[t$95$0, 2.0], $MachinePrecision] + N[(N[Power[x, 1/3], $MachinePrecision] * N[(t$95$0 + N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt[3]{1 + x}\\
\frac{1}{{t\_0}^{2} + \sqrt[3]{x} \cdot \left(t\_0 + \sqrt[3]{x}\right)}
\end{array}
\end{array}
Initial program 7.7%
flip3--8.1%
div-inv8.1%
rem-cube-cbrt8.2%
rem-cube-cbrt11.3%
+-commutative11.3%
distribute-rgt-out11.2%
+-commutative11.2%
fma-define11.2%
add-exp-log11.2%
Applied egg-rr11.2%
associate-*r/11.2%
*-rgt-identity11.2%
+-commutative11.2%
associate--l+93.3%
+-inverses93.3%
metadata-eval93.3%
+-commutative93.3%
exp-prod92.6%
Simplified92.6%
pow-exp93.3%
*-commutative93.3%
log1p-undefine93.3%
+-commutative93.3%
exp-to-pow93.1%
metadata-eval93.1%
pow-sqr93.1%
pow1/394.5%
pow1/398.5%
cbrt-unprod52.9%
pow252.9%
Applied egg-rr52.9%
fma-undefine52.9%
+-commutative52.9%
pow1/351.4%
add-exp-log51.7%
log1p-undefine51.7%
exp-prod51.4%
distribute-rgt-in51.4%
+-commutative51.4%
unpow251.4%
cbrt-unprod94.6%
pow294.6%
distribute-rgt-in94.6%
+-commutative94.6%
Applied egg-rr98.4%
Final simplification98.4%
(FPCore (x) :precision binary64 (/ 1.0 (fma (cbrt x) (+ (cbrt (+ 1.0 x)) (cbrt x)) (pow (+ 1.0 x) 0.6666666666666666))))
double code(double x) {
return 1.0 / fma(cbrt(x), (cbrt((1.0 + x)) + cbrt(x)), pow((1.0 + x), 0.6666666666666666));
}
function code(x) return Float64(1.0 / fma(cbrt(x), Float64(cbrt(Float64(1.0 + x)) + cbrt(x)), (Float64(1.0 + x) ^ 0.6666666666666666))) end
code[x_] := N[(1.0 / N[(N[Power[x, 1/3], $MachinePrecision] * N[(N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] + N[Power[N[(1.0 + x), $MachinePrecision], 0.6666666666666666], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\mathsf{fma}\left(\sqrt[3]{x}, \sqrt[3]{1 + x} + \sqrt[3]{x}, {\left(1 + x\right)}^{0.6666666666666666}\right)}
\end{array}
Initial program 7.7%
flip3--8.1%
div-inv8.1%
rem-cube-cbrt8.2%
rem-cube-cbrt11.3%
+-commutative11.3%
distribute-rgt-out11.2%
+-commutative11.2%
fma-define11.2%
add-exp-log11.2%
Applied egg-rr11.2%
associate-*r/11.2%
*-rgt-identity11.2%
+-commutative11.2%
associate--l+93.3%
+-inverses93.3%
metadata-eval93.3%
+-commutative93.3%
exp-prod92.6%
Simplified92.6%
pow-exp93.3%
*-commutative93.3%
log1p-undefine93.3%
+-commutative93.3%
exp-to-pow93.1%
metadata-eval93.1%
pow-sqr93.1%
pow1/394.5%
pow1/398.5%
Applied egg-rr98.5%
pow298.5%
pow1/393.1%
pow-pow93.1%
metadata-eval93.1%
Applied egg-rr93.1%
Final simplification93.1%
(FPCore (x)
:precision binary64
(if (<= x 6e+76)
(/
(+
(* (cbrt x) -0.1111111111111111)
(* 0.3333333333333333 (cbrt (pow x 4.0))))
(pow x 2.0))
(if (<= x 1.4e+154)
(* 0.3333333333333333 (cbrt (/ 1.0 (pow x 2.0))))
(/ 1.0 (fma (cbrt x) (+ (cbrt (+ 1.0 x)) (cbrt x)) 1.0)))))
double code(double x) {
double tmp;
if (x <= 6e+76) {
tmp = ((cbrt(x) * -0.1111111111111111) + (0.3333333333333333 * cbrt(pow(x, 4.0)))) / pow(x, 2.0);
} else if (x <= 1.4e+154) {
tmp = 0.3333333333333333 * cbrt((1.0 / pow(x, 2.0)));
} else {
tmp = 1.0 / fma(cbrt(x), (cbrt((1.0 + x)) + cbrt(x)), 1.0);
}
return tmp;
}
function code(x) tmp = 0.0 if (x <= 6e+76) tmp = Float64(Float64(Float64(cbrt(x) * -0.1111111111111111) + Float64(0.3333333333333333 * cbrt((x ^ 4.0)))) / (x ^ 2.0)); elseif (x <= 1.4e+154) tmp = Float64(0.3333333333333333 * cbrt(Float64(1.0 / (x ^ 2.0)))); else tmp = Float64(1.0 / fma(cbrt(x), Float64(cbrt(Float64(1.0 + x)) + cbrt(x)), 1.0)); end return tmp end
code[x_] := If[LessEqual[x, 6e+76], N[(N[(N[(N[Power[x, 1/3], $MachinePrecision] * -0.1111111111111111), $MachinePrecision] + N[(0.3333333333333333 * N[Power[N[Power[x, 4.0], $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.4e+154], N[(0.3333333333333333 * N[Power[N[(1.0 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision], N[(1.0 / N[(N[Power[x, 1/3], $MachinePrecision] * N[(N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;x \leq 6 \cdot 10^{+76}:\\
\;\;\;\;\frac{\sqrt[3]{x} \cdot -0.1111111111111111 + 0.3333333333333333 \cdot \sqrt[3]{{x}^{4}}}{{x}^{2}}\\
\mathbf{elif}\;x \leq 1.4 \cdot 10^{+154}:\\
\;\;\;\;0.3333333333333333 \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\\
\mathbf{else}:\\
\;\;\;\;\frac{1}{\mathsf{fma}\left(\sqrt[3]{x}, \sqrt[3]{1 + x} + \sqrt[3]{x}, 1\right)}\\
\end{array}
\end{array}
if x < 5.9999999999999996e76Initial program 17.2%
Taylor expanded in x around inf 97.1%
if 5.9999999999999996e76 < x < 1.4e154Initial program 3.8%
Taylor expanded in x around inf 98.9%
if 1.4e154 < x Initial program 4.8%
flip3--4.8%
div-inv4.8%
rem-cube-cbrt3.1%
rem-cube-cbrt4.8%
+-commutative4.8%
distribute-rgt-out4.8%
+-commutative4.8%
fma-define4.8%
add-exp-log4.8%
Applied egg-rr4.8%
associate-*r/4.8%
*-rgt-identity4.8%
+-commutative4.8%
associate--l+91.9%
+-inverses91.9%
metadata-eval91.9%
+-commutative91.9%
exp-prod90.9%
Simplified90.9%
Taylor expanded in x around 0 19.9%
Final simplification59.9%
(FPCore (x) :precision binary64 (if (<= x 1.4e+154) (* 0.3333333333333333 (cbrt (/ 1.0 (pow x 2.0)))) (/ 1.0 (fma (cbrt x) (+ (cbrt (+ 1.0 x)) (cbrt x)) 1.0))))
double code(double x) {
double tmp;
if (x <= 1.4e+154) {
tmp = 0.3333333333333333 * cbrt((1.0 / pow(x, 2.0)));
} else {
tmp = 1.0 / fma(cbrt(x), (cbrt((1.0 + x)) + cbrt(x)), 1.0);
}
return tmp;
}
function code(x) tmp = 0.0 if (x <= 1.4e+154) tmp = Float64(0.3333333333333333 * cbrt(Float64(1.0 / (x ^ 2.0)))); else tmp = Float64(1.0 / fma(cbrt(x), Float64(cbrt(Float64(1.0 + x)) + cbrt(x)), 1.0)); end return tmp end
code[x_] := If[LessEqual[x, 1.4e+154], N[(0.3333333333333333 * N[Power[N[(1.0 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision], N[(1.0 / N[(N[Power[x, 1/3], $MachinePrecision] * N[(N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;x \leq 1.4 \cdot 10^{+154}:\\
\;\;\;\;0.3333333333333333 \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\\
\mathbf{else}:\\
\;\;\;\;\frac{1}{\mathsf{fma}\left(\sqrt[3]{x}, \sqrt[3]{1 + x} + \sqrt[3]{x}, 1\right)}\\
\end{array}
\end{array}
if x < 1.4e154Initial program 10.4%
Taylor expanded in x around inf 94.5%
if 1.4e154 < x Initial program 4.8%
flip3--4.8%
div-inv4.8%
rem-cube-cbrt3.1%
rem-cube-cbrt4.8%
+-commutative4.8%
distribute-rgt-out4.8%
+-commutative4.8%
fma-define4.8%
add-exp-log4.8%
Applied egg-rr4.8%
associate-*r/4.8%
*-rgt-identity4.8%
+-commutative4.8%
associate--l+91.9%
+-inverses91.9%
metadata-eval91.9%
+-commutative91.9%
exp-prod90.9%
Simplified90.9%
Taylor expanded in x around 0 19.9%
Final simplification58.1%
(FPCore (x) :precision binary64 (if (<= x 1.4e+154) (* 0.3333333333333333 (cbrt (/ 1.0 (pow x 2.0)))) (/ 1.0 (+ 1.0 (* (cbrt x) (+ 1.0 (cbrt x)))))))
double code(double x) {
double tmp;
if (x <= 1.4e+154) {
tmp = 0.3333333333333333 * cbrt((1.0 / pow(x, 2.0)));
} else {
tmp = 1.0 / (1.0 + (cbrt(x) * (1.0 + cbrt(x))));
}
return tmp;
}
public static double code(double x) {
double tmp;
if (x <= 1.4e+154) {
tmp = 0.3333333333333333 * Math.cbrt((1.0 / Math.pow(x, 2.0)));
} else {
tmp = 1.0 / (1.0 + (Math.cbrt(x) * (1.0 + Math.cbrt(x))));
}
return tmp;
}
function code(x) tmp = 0.0 if (x <= 1.4e+154) tmp = Float64(0.3333333333333333 * cbrt(Float64(1.0 / (x ^ 2.0)))); else tmp = Float64(1.0 / Float64(1.0 + Float64(cbrt(x) * Float64(1.0 + cbrt(x))))); end return tmp end
code[x_] := If[LessEqual[x, 1.4e+154], N[(0.3333333333333333 * N[Power[N[(1.0 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision], N[(1.0 / N[(1.0 + N[(N[Power[x, 1/3], $MachinePrecision] * N[(1.0 + N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;x \leq 1.4 \cdot 10^{+154}:\\
\;\;\;\;0.3333333333333333 \cdot \sqrt[3]{\frac{1}{{x}^{2}}}\\
\mathbf{else}:\\
\;\;\;\;\frac{1}{1 + \sqrt[3]{x} \cdot \left(1 + \sqrt[3]{x}\right)}\\
\end{array}
\end{array}
if x < 1.4e154Initial program 10.4%
Taylor expanded in x around inf 94.5%
if 1.4e154 < x Initial program 4.8%
flip3--4.8%
div-inv4.8%
rem-cube-cbrt3.1%
rem-cube-cbrt4.8%
+-commutative4.8%
distribute-rgt-out4.8%
+-commutative4.8%
fma-define4.8%
add-exp-log4.8%
Applied egg-rr4.8%
associate-*r/4.8%
*-rgt-identity4.8%
+-commutative4.8%
associate--l+91.9%
+-inverses91.9%
metadata-eval91.9%
+-commutative91.9%
exp-prod90.9%
Simplified90.9%
pow-exp91.9%
*-commutative91.9%
log1p-undefine91.9%
+-commutative91.9%
exp-to-pow91.5%
metadata-eval91.5%
pow-sqr91.5%
pow1/393.1%
pow1/398.5%
cbrt-unprod4.8%
pow24.8%
Applied egg-rr4.8%
Taylor expanded in x around 0 17.7%
Final simplification57.0%
(FPCore (x) :precision binary64 (+ (cbrt x) (- 0.0 (pow x 0.3333333333333333))))
double code(double x) {
return cbrt(x) + (0.0 - pow(x, 0.3333333333333333));
}
public static double code(double x) {
return Math.cbrt(x) + (0.0 - Math.pow(x, 0.3333333333333333));
}
function code(x) return Float64(cbrt(x) + Float64(0.0 - (x ^ 0.3333333333333333))) end
code[x_] := N[(N[Power[x, 1/3], $MachinePrecision] + N[(0.0 - N[Power[x, 0.3333333333333333], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt[3]{x} + \left(0 - {x}^{0.3333333333333333}\right)
\end{array}
Initial program 7.7%
Taylor expanded in x around inf 4.2%
pow1/35.8%
Applied egg-rr5.8%
Final simplification5.8%
(FPCore (x) :precision binary64 (* 0.3333333333333333 (cbrt (/ 1.0 (pow x 2.0)))))
double code(double x) {
return 0.3333333333333333 * cbrt((1.0 / pow(x, 2.0)));
}
public static double code(double x) {
return 0.3333333333333333 * Math.cbrt((1.0 / Math.pow(x, 2.0)));
}
function code(x) return Float64(0.3333333333333333 * cbrt(Float64(1.0 / (x ^ 2.0)))) end
code[x_] := N[(0.3333333333333333 * N[Power[N[(1.0 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.3333333333333333 \cdot \sqrt[3]{\frac{1}{{x}^{2}}}
\end{array}
Initial program 7.7%
Taylor expanded in x around inf 50.7%
Final simplification50.7%
(FPCore (x) :precision binary64 (- (cbrt (+ 1.0 x)) (cbrt x)))
double code(double x) {
return cbrt((1.0 + x)) - cbrt(x);
}
public static double code(double x) {
return Math.cbrt((1.0 + x)) - Math.cbrt(x);
}
function code(x) return Float64(cbrt(Float64(1.0 + x)) - cbrt(x)) end
code[x_] := N[(N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt[3]{1 + x} - \sqrt[3]{x}
\end{array}
Initial program 7.7%
Final simplification7.7%
(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}
Initial program 7.7%
Taylor expanded in x around 0 1.8%
sub-neg1.8%
rem-square-sqrt0.0%
fabs-sqr0.0%
rem-square-sqrt5.4%
fabs-neg5.4%
unpow1/35.4%
metadata-eval5.4%
pow-sqr5.4%
fabs-sqr5.4%
pow-sqr5.4%
metadata-eval5.4%
unpow1/35.4%
Simplified5.4%
Final simplification5.4%
(FPCore (x) :precision binary64 (let* ((t_0 (cbrt (+ x 1.0)))) (/ 1.0 (+ (+ (* t_0 t_0) (* (cbrt x) t_0)) (* (cbrt x) (cbrt x))))))
double code(double x) {
double t_0 = cbrt((x + 1.0));
return 1.0 / (((t_0 * t_0) + (cbrt(x) * t_0)) + (cbrt(x) * cbrt(x)));
}
public static double code(double x) {
double t_0 = Math.cbrt((x + 1.0));
return 1.0 / (((t_0 * t_0) + (Math.cbrt(x) * t_0)) + (Math.cbrt(x) * Math.cbrt(x)));
}
function code(x) t_0 = cbrt(Float64(x + 1.0)) return Float64(1.0 / Float64(Float64(Float64(t_0 * t_0) + Float64(cbrt(x) * t_0)) + Float64(cbrt(x) * cbrt(x)))) end
code[x_] := Block[{t$95$0 = N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision]}, N[(1.0 / N[(N[(N[(t$95$0 * t$95$0), $MachinePrecision] + N[(N[Power[x, 1/3], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(N[Power[x, 1/3], $MachinePrecision] * N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt[3]{x + 1}\\
\frac{1}{\left(t\_0 \cdot t\_0 + \sqrt[3]{x} \cdot t\_0\right) + \sqrt[3]{x} \cdot \sqrt[3]{x}}
\end{array}
\end{array}
herbie shell --seed 2024089
(FPCore (x)
:name "2cbrt (problem 3.3.4)"
:precision binary64
:pre (and (> x 1.0) (< x 1e+308))
:alt
(/ 1.0 (+ (+ (* (cbrt (+ x 1.0)) (cbrt (+ x 1.0))) (* (cbrt x) (cbrt (+ x 1.0)))) (* (cbrt x) (cbrt x))))
(- (cbrt (+ x 1.0)) (cbrt x)))