
(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 9 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
(if (<= x 1e+43)
(/
1.0
(+
(pow (cbrt (+ 1.0 x)) 2.0)
(+ (pow (cbrt x) 2.0) (cbrt (* x (+ 1.0 x))))))
(/
(/ 1.0 x)
(fma 2.0 (cbrt (/ 1.0 x)) (cbrt (+ (/ 1.0 x) (/ 2.0 (pow x 2.0))))))))
double code(double x) {
double tmp;
if (x <= 1e+43) {
tmp = 1.0 / (pow(cbrt((1.0 + x)), 2.0) + (pow(cbrt(x), 2.0) + cbrt((x * (1.0 + x)))));
} else {
tmp = (1.0 / x) / fma(2.0, cbrt((1.0 / x)), cbrt(((1.0 / x) + (2.0 / pow(x, 2.0)))));
}
return tmp;
}
function code(x) tmp = 0.0 if (x <= 1e+43) tmp = Float64(1.0 / Float64((cbrt(Float64(1.0 + x)) ^ 2.0) + Float64((cbrt(x) ^ 2.0) + cbrt(Float64(x * Float64(1.0 + x)))))); else tmp = Float64(Float64(1.0 / x) / fma(2.0, cbrt(Float64(1.0 / x)), cbrt(Float64(Float64(1.0 / x) + Float64(2.0 / (x ^ 2.0)))))); end return tmp end
code[x_] := If[LessEqual[x, 1e+43], N[(1.0 / N[(N[Power[N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Power[N[Power[x, 1/3], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(x * N[(1.0 + x), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(1.0 / x), $MachinePrecision] / N[(2.0 * N[Power[N[(1.0 / x), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[N[(N[(1.0 / x), $MachinePrecision] + N[(2.0 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;x \leq 10^{+43}:\\
\;\;\;\;\frac{1}{{\left(\sqrt[3]{1 + x}\right)}^{2} + \left({\left(\sqrt[3]{x}\right)}^{2} + \sqrt[3]{x \cdot \left(1 + x\right)}\right)}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{1}{x}}{\mathsf{fma}\left(2, \sqrt[3]{\frac{1}{x}}, \sqrt[3]{\frac{1}{x} + \frac{2}{{x}^{2}}}\right)}\\
\end{array}
\end{array}
if x < 1.00000000000000001e43Initial program 30.0%
add-exp-log30.4%
Applied egg-rr30.4%
rem-exp-log30.0%
flip3--30.0%
+-commutative30.0%
rem-cube-cbrt30.7%
rem-cube-cbrt52.5%
associate-+r-98.9%
+-inverses98.9%
metadata-eval98.9%
+-commutative98.9%
+-commutative98.9%
unpow298.9%
pow298.9%
+-commutative98.9%
cbrt-unprod99.0%
Applied egg-rr99.0%
+-commutative99.0%
*-commutative99.0%
+-commutative99.0%
Simplified99.0%
if 1.00000000000000001e43 < x Initial program 4.3%
flip3--4.3%
div-inv4.3%
rem-cube-cbrt3.4%
rem-cube-cbrt4.3%
+-commutative4.3%
distribute-rgt-out4.3%
+-commutative4.3%
fma-define4.3%
add-exp-log4.3%
Applied egg-rr4.3%
associate-*r/4.3%
*-rgt-identity4.3%
+-commutative4.3%
associate--l+92.7%
+-commutative92.7%
+-commutative92.7%
Simplified92.7%
*-commutative92.7%
exp-prod92.8%
log1p-undefine92.8%
add-exp-log92.4%
+-commutative92.4%
metadata-eval92.4%
pow-sqr92.4%
pow1/393.9%
pow1/398.5%
pow298.5%
+-commutative98.5%
Applied egg-rr98.5%
Taylor expanded in x around inf 20.6%
Taylor expanded in x around inf 98.7%
associate-/r*98.8%
+-commutative98.8%
fma-define98.8%
associate-*r/98.8%
metadata-eval98.8%
Simplified98.8%
Final simplification98.9%
(FPCore (x) :precision binary64 (let* ((t_0 (cbrt (+ 1.0 x)))) (/ 1.0 (fma (cbrt x) (+ (cbrt x) t_0) (pow t_0 2.0)))))
double code(double x) {
double t_0 = cbrt((1.0 + x));
return 1.0 / fma(cbrt(x), (cbrt(x) + t_0), pow(t_0, 2.0));
}
function code(x) t_0 = cbrt(Float64(1.0 + x)) return Float64(1.0 / fma(cbrt(x), Float64(cbrt(x) + t_0), (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[(N[Power[x, 1/3], $MachinePrecision] + t$95$0), $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}, \sqrt[3]{x} + t\_0, {t\_0}^{2}\right)}
\end{array}
\end{array}
Initial program 8.0%
flip3--8.0%
div-inv8.0%
rem-cube-cbrt7.3%
rem-cube-cbrt11.3%
+-commutative11.3%
distribute-rgt-out11.3%
+-commutative11.3%
fma-define11.3%
add-exp-log11.2%
Applied egg-rr11.2%
associate-*r/11.2%
*-rgt-identity11.2%
+-commutative11.2%
associate--l+93.3%
+-commutative93.3%
+-commutative93.3%
Simplified93.3%
*-commutative93.3%
exp-prod93.5%
log1p-undefine93.5%
add-exp-log93.1%
+-commutative93.1%
metadata-eval93.1%
pow-sqr93.1%
pow1/394.5%
pow1/398.5%
pow298.5%
+-commutative98.5%
Applied egg-rr98.5%
Taylor expanded in x around 0 98.5%
(FPCore (x) :precision binary64 (let* ((t_0 (cbrt (+ 1.0 x)))) (/ (+ 1.0 (- x x)) (+ (pow t_0 2.0) (* (cbrt x) (+ (cbrt x) t_0))))))
double code(double x) {
double t_0 = cbrt((1.0 + x));
return (1.0 + (x - x)) / (pow(t_0, 2.0) + (cbrt(x) * (cbrt(x) + t_0)));
}
public static double code(double x) {
double t_0 = Math.cbrt((1.0 + x));
return (1.0 + (x - x)) / (Math.pow(t_0, 2.0) + (Math.cbrt(x) * (Math.cbrt(x) + t_0)));
}
function code(x) t_0 = cbrt(Float64(1.0 + x)) return Float64(Float64(1.0 + Float64(x - x)) / Float64((t_0 ^ 2.0) + Float64(cbrt(x) * Float64(cbrt(x) + t_0)))) end
code[x_] := Block[{t$95$0 = N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision]}, N[(N[(1.0 + N[(x - x), $MachinePrecision]), $MachinePrecision] / N[(N[Power[t$95$0, 2.0], $MachinePrecision] + N[(N[Power[x, 1/3], $MachinePrecision] * N[(N[Power[x, 1/3], $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt[3]{1 + x}\\
\frac{1 + \left(x - x\right)}{{t\_0}^{2} + \sqrt[3]{x} \cdot \left(\sqrt[3]{x} + t\_0\right)}
\end{array}
\end{array}
Initial program 8.0%
flip3--8.0%
div-inv8.0%
rem-cube-cbrt7.3%
rem-cube-cbrt11.3%
+-commutative11.3%
distribute-rgt-out11.3%
+-commutative11.3%
fma-define11.3%
add-exp-log11.2%
Applied egg-rr11.2%
associate-*r/11.2%
*-rgt-identity11.2%
+-commutative11.2%
associate--l+93.3%
+-commutative93.3%
+-commutative93.3%
Simplified93.3%
*-commutative93.3%
exp-prod93.5%
log1p-undefine93.5%
add-exp-log93.1%
+-commutative93.1%
metadata-eval93.1%
pow-sqr93.1%
pow1/394.5%
pow1/398.5%
pow298.5%
+-commutative98.5%
Applied egg-rr98.5%
add-cube-cbrt98.4%
pow398.4%
Applied egg-rr98.4%
fma-undefine98.5%
rem-cube-cbrt98.5%
Applied egg-rr98.5%
Final simplification98.5%
(FPCore (x) :precision binary64 (/ (/ 1.0 x) (fma 2.0 (cbrt (/ 1.0 x)) (cbrt (+ (/ 1.0 x) (/ 2.0 (pow x 2.0)))))))
double code(double x) {
return (1.0 / x) / fma(2.0, cbrt((1.0 / x)), cbrt(((1.0 / x) + (2.0 / pow(x, 2.0)))));
}
function code(x) return Float64(Float64(1.0 / x) / fma(2.0, cbrt(Float64(1.0 / x)), cbrt(Float64(Float64(1.0 / x) + Float64(2.0 / (x ^ 2.0)))))) end
code[x_] := N[(N[(1.0 / x), $MachinePrecision] / N[(2.0 * N[Power[N[(1.0 / x), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[N[(N[(1.0 / x), $MachinePrecision] + N[(2.0 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{1}{x}}{\mathsf{fma}\left(2, \sqrt[3]{\frac{1}{x}}, \sqrt[3]{\frac{1}{x} + \frac{2}{{x}^{2}}}\right)}
\end{array}
Initial program 8.0%
flip3--8.0%
div-inv8.0%
rem-cube-cbrt7.3%
rem-cube-cbrt11.3%
+-commutative11.3%
distribute-rgt-out11.3%
+-commutative11.3%
fma-define11.3%
add-exp-log11.2%
Applied egg-rr11.2%
associate-*r/11.2%
*-rgt-identity11.2%
+-commutative11.2%
associate--l+93.3%
+-commutative93.3%
+-commutative93.3%
Simplified93.3%
*-commutative93.3%
exp-prod93.5%
log1p-undefine93.5%
add-exp-log93.1%
+-commutative93.1%
metadata-eval93.1%
pow-sqr93.1%
pow1/394.5%
pow1/398.5%
pow298.5%
+-commutative98.5%
Applied egg-rr98.5%
Taylor expanded in x around inf 29.4%
Taylor expanded in x around inf 96.3%
associate-/r*96.4%
+-commutative96.4%
fma-define96.4%
associate-*r/96.4%
metadata-eval96.4%
Simplified96.4%
(FPCore (x) :precision binary64 (/ 1.0 (* x (+ (cbrt (+ (/ 1.0 x) (/ 2.0 (pow x 2.0)))) (* 2.0 (cbrt (/ 1.0 x)))))))
double code(double x) {
return 1.0 / (x * (cbrt(((1.0 / x) + (2.0 / pow(x, 2.0)))) + (2.0 * cbrt((1.0 / x)))));
}
public static double code(double x) {
return 1.0 / (x * (Math.cbrt(((1.0 / x) + (2.0 / Math.pow(x, 2.0)))) + (2.0 * Math.cbrt((1.0 / x)))));
}
function code(x) return Float64(1.0 / Float64(x * Float64(cbrt(Float64(Float64(1.0 / x) + Float64(2.0 / (x ^ 2.0)))) + Float64(2.0 * cbrt(Float64(1.0 / x)))))) end
code[x_] := N[(1.0 / N[(x * N[(N[Power[N[(N[(1.0 / x), $MachinePrecision] + N[(2.0 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision] + N[(2.0 * N[Power[N[(1.0 / x), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{x \cdot \left(\sqrt[3]{\frac{1}{x} + \frac{2}{{x}^{2}}} + 2 \cdot \sqrt[3]{\frac{1}{x}}\right)}
\end{array}
Initial program 8.0%
flip3--8.0%
div-inv8.0%
rem-cube-cbrt7.3%
rem-cube-cbrt11.3%
+-commutative11.3%
distribute-rgt-out11.3%
+-commutative11.3%
fma-define11.3%
add-exp-log11.2%
Applied egg-rr11.2%
associate-*r/11.2%
*-rgt-identity11.2%
+-commutative11.2%
associate--l+93.3%
+-commutative93.3%
+-commutative93.3%
Simplified93.3%
*-commutative93.3%
exp-prod93.5%
log1p-undefine93.5%
add-exp-log93.1%
+-commutative93.1%
metadata-eval93.1%
pow-sqr93.1%
pow1/394.5%
pow1/398.5%
pow298.5%
+-commutative98.5%
Applied egg-rr98.5%
Taylor expanded in x around inf 29.4%
Taylor expanded in x around inf 96.3%
associate-*r/96.3%
metadata-eval96.3%
Simplified96.3%
(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 8.0%
add-exp-log7.0%
+-commutative7.0%
log1p-define7.0%
Applied egg-rr7.0%
log1p-undefine7.0%
add-exp-log8.0%
+-commutative8.0%
add-exp-log7.4%
pow1/36.0%
log-pow6.2%
+-commutative6.2%
log1p-undefine6.2%
Applied egg-rr6.2%
Simplified6.3%
Taylor expanded in x around inf 50.6%
(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 8.0%
Final simplification8.0%
(FPCore (x) :precision binary64 (+ (cbrt x) (cbrt (+ 1.0 x))))
double code(double x) {
return cbrt(x) + cbrt((1.0 + x));
}
public static double code(double x) {
return Math.cbrt(x) + Math.cbrt((1.0 + x));
}
function code(x) return Float64(cbrt(x) + cbrt(Float64(1.0 + x))) end
code[x_] := N[(N[Power[x, 1/3], $MachinePrecision] + N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt[3]{x} + \sqrt[3]{1 + x}
\end{array}
Initial program 8.0%
sub-neg8.0%
Applied egg-rr8.0%
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%
+-commutative5.4%
Simplified5.4%
Final simplification5.4%
(FPCore (x) :precision binary64 (- (* x 0.3333333333333333) (cbrt x)))
double code(double x) {
return (x * 0.3333333333333333) - cbrt(x);
}
public static double code(double x) {
return (x * 0.3333333333333333) - Math.cbrt(x);
}
function code(x) return Float64(Float64(x * 0.3333333333333333) - cbrt(x)) end
code[x_] := N[(N[(x * 0.3333333333333333), $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
x \cdot 0.3333333333333333 - \sqrt[3]{x}
\end{array}
Initial program 8.0%
add-exp-log7.0%
+-commutative7.0%
log1p-define7.0%
Applied egg-rr7.0%
Taylor expanded in x around 0 4.3%
Simplified4.3%
(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 2024179
(FPCore (x)
:name "2cbrt (problem 3.3.4)"
:precision binary64
:pre (and (> x 1.0) (< x 1e+308))
:alt
(! :herbie-platform default (/ 1 (+ (* (cbrt (+ x 1)) (cbrt (+ x 1))) (* (cbrt x) (cbrt (+ x 1))) (* (cbrt x) (cbrt x)))))
(- (cbrt (+ x 1.0)) (cbrt x)))