
(FPCore (x) :precision binary64 (- (/ 1.0 (sqrt x)) (/ 1.0 (sqrt (+ x 1.0)))))
double code(double x) {
return (1.0 / sqrt(x)) - (1.0 / sqrt((x + 1.0)));
}
real(8) function code(x)
real(8), intent (in) :: x
code = (1.0d0 / sqrt(x)) - (1.0d0 / sqrt((x + 1.0d0)))
end function
public static double code(double x) {
return (1.0 / Math.sqrt(x)) - (1.0 / Math.sqrt((x + 1.0)));
}
def code(x): return (1.0 / math.sqrt(x)) - (1.0 / math.sqrt((x + 1.0)))
function code(x) return Float64(Float64(1.0 / sqrt(x)) - Float64(1.0 / sqrt(Float64(x + 1.0)))) end
function tmp = code(x) tmp = (1.0 / sqrt(x)) - (1.0 / sqrt((x + 1.0))); end
code[x_] := N[(N[(1.0 / N[Sqrt[x], $MachinePrecision]), $MachinePrecision] - N[(1.0 / N[Sqrt[N[(x + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\sqrt{x}} - \frac{1}{\sqrt{x + 1}}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 8 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (x) :precision binary64 (- (/ 1.0 (sqrt x)) (/ 1.0 (sqrt (+ x 1.0)))))
double code(double x) {
return (1.0 / sqrt(x)) - (1.0 / sqrt((x + 1.0)));
}
real(8) function code(x)
real(8), intent (in) :: x
code = (1.0d0 / sqrt(x)) - (1.0d0 / sqrt((x + 1.0d0)))
end function
public static double code(double x) {
return (1.0 / Math.sqrt(x)) - (1.0 / Math.sqrt((x + 1.0)));
}
def code(x): return (1.0 / math.sqrt(x)) - (1.0 / math.sqrt((x + 1.0)))
function code(x) return Float64(Float64(1.0 / sqrt(x)) - Float64(1.0 / sqrt(Float64(x + 1.0)))) end
function tmp = code(x) tmp = (1.0 / sqrt(x)) - (1.0 / sqrt((x + 1.0))); end
code[x_] := N[(N[(1.0 / N[Sqrt[x], $MachinePrecision]), $MachinePrecision] - N[(1.0 / N[Sqrt[N[(x + 1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\sqrt{x}} - \frac{1}{\sqrt{x + 1}}
\end{array}
(FPCore (x) :precision binary64 (/ (- (sqrt (/ 1.0 x))) (fma (sqrt (+ 1.0 x)) (- (sqrt x)) (fma -1.0 x -1.0))))
double code(double x) {
return -sqrt((1.0 / x)) / fma(sqrt((1.0 + x)), -sqrt(x), fma(-1.0, x, -1.0));
}
function code(x) return Float64(Float64(-sqrt(Float64(1.0 / x))) / fma(sqrt(Float64(1.0 + x)), Float64(-sqrt(x)), fma(-1.0, x, -1.0))) end
code[x_] := N[((-N[Sqrt[N[(1.0 / x), $MachinePrecision]], $MachinePrecision]) / N[(N[Sqrt[N[(1.0 + x), $MachinePrecision]], $MachinePrecision] * (-N[Sqrt[x], $MachinePrecision]) + N[(-1.0 * x + -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{-\sqrt{\frac{1}{x}}}{\mathsf{fma}\left(\sqrt{1 + x}, -\sqrt{x}, \mathsf{fma}\left(-1, x, -1\right)\right)}
\end{array}
Initial program 39.5%
lift--.f64N/A
lift-/.f64N/A
lift-/.f64N/A
frac-subN/A
div-invN/A
metadata-evalN/A
div-invN/A
*-lft-identityN/A
flip--N/A
metadata-evalN/A
frac-timesN/A
frac-2negN/A
metadata-evalN/A
lift-/.f64N/A
associate-*r/N/A
Applied rewrites40.7%
Taylor expanded in x around 0
mul-1-negN/A
lower-neg.f64N/A
lower-sqrt.f64N/A
lower-/.f6499.3
Applied rewrites99.3%
lift-*.f64N/A
*-commutativeN/A
lift-+.f64N/A
+-commutativeN/A
distribute-rgt-inN/A
lower-fma.f64N/A
lift-+.f64N/A
+-commutativeN/A
lower-+.f64N/A
lift-+.f64N/A
+-commutativeN/A
lower-+.f64N/A
lower-*.f6499.3
lift-+.f64N/A
+-commutativeN/A
lower-+.f6499.3
Applied rewrites99.3%
lift-fma.f64N/A
+-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-neg.f64N/A
distribute-lft-neg-inN/A
distribute-rgt-neg-inN/A
lower-fma.f64N/A
lift-+.f64N/A
+-commutativeN/A
lower-+.f64N/A
lower-neg.f64N/A
lift-neg.f64N/A
distribute-rgt-neg-outN/A
pow2N/A
lift-sqrt.f64N/A
pow1/2N/A
lift-+.f64N/A
+-commutativeN/A
pow-powN/A
Applied rewrites99.6%
Final simplification99.6%
(FPCore (x) :precision binary64 (/ (- (sqrt (/ 1.0 x))) (fma (/ 0.125 (* x x)) x (fma -2.0 x -1.5))))
double code(double x) {
return -sqrt((1.0 / x)) / fma((0.125 / (x * x)), x, fma(-2.0, x, -1.5));
}
function code(x) return Float64(Float64(-sqrt(Float64(1.0 / x))) / fma(Float64(0.125 / Float64(x * x)), x, fma(-2.0, x, -1.5))) end
code[x_] := N[((-N[Sqrt[N[(1.0 / x), $MachinePrecision]], $MachinePrecision]) / N[(N[(0.125 / N[(x * x), $MachinePrecision]), $MachinePrecision] * x + N[(-2.0 * x + -1.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{-\sqrt{\frac{1}{x}}}{\mathsf{fma}\left(\frac{0.125}{x \cdot x}, x, \mathsf{fma}\left(-2, x, -1.5\right)\right)}
\end{array}
Initial program 39.5%
lift--.f64N/A
lift-/.f64N/A
lift-/.f64N/A
frac-subN/A
div-invN/A
metadata-evalN/A
div-invN/A
*-lft-identityN/A
flip--N/A
metadata-evalN/A
frac-timesN/A
frac-2negN/A
metadata-evalN/A
lift-/.f64N/A
associate-*r/N/A
Applied rewrites40.7%
Taylor expanded in x around 0
mul-1-negN/A
lower-neg.f64N/A
lower-sqrt.f64N/A
lower-/.f6499.3
Applied rewrites99.3%
lift-*.f64N/A
*-commutativeN/A
lift-+.f64N/A
+-commutativeN/A
distribute-rgt-inN/A
lower-fma.f64N/A
lift-+.f64N/A
+-commutativeN/A
lower-+.f64N/A
lift-+.f64N/A
+-commutativeN/A
lower-+.f64N/A
lower-*.f6499.3
lift-+.f64N/A
+-commutativeN/A
lower-+.f6499.3
Applied rewrites99.3%
Taylor expanded in x around inf
sub-negN/A
distribute-rgt-inN/A
distribute-lft-neg-inN/A
*-commutativeN/A
mul-1-negN/A
lower-fma.f64N/A
lower-/.f64N/A
unpow2N/A
lower-*.f64N/A
distribute-rgt-inN/A
distribute-rgt-inN/A
metadata-evalN/A
metadata-evalN/A
rem-square-sqrtN/A
unpow2N/A
*-commutativeN/A
Applied rewrites99.1%
(FPCore (x) :precision binary64 (/ (/ (+ 0.5 (/ (- (/ 0.3125 x) 0.375) x)) x) (sqrt x)))
double code(double x) {
return ((0.5 + (((0.3125 / x) - 0.375) / x)) / x) / sqrt(x);
}
real(8) function code(x)
real(8), intent (in) :: x
code = ((0.5d0 + (((0.3125d0 / x) - 0.375d0) / x)) / x) / sqrt(x)
end function
public static double code(double x) {
return ((0.5 + (((0.3125 / x) - 0.375) / x)) / x) / Math.sqrt(x);
}
def code(x): return ((0.5 + (((0.3125 / x) - 0.375) / x)) / x) / math.sqrt(x)
function code(x) return Float64(Float64(Float64(0.5 + Float64(Float64(Float64(0.3125 / x) - 0.375) / x)) / x) / sqrt(x)) end
function tmp = code(x) tmp = ((0.5 + (((0.3125 / x) - 0.375) / x)) / x) / sqrt(x); end
code[x_] := N[(N[(N[(0.5 + N[(N[(N[(0.3125 / x), $MachinePrecision] - 0.375), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision] / N[Sqrt[x], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{0.5 + \frac{\frac{0.3125}{x} - 0.375}{x}}{x}}{\sqrt{x}}
\end{array}
Initial program 39.5%
lift--.f64N/A
lift-/.f64N/A
clear-numN/A
lift-/.f64N/A
frac-subN/A
div-invN/A
metadata-evalN/A
*-rgt-identityN/A
*-commutativeN/A
associate-/r*N/A
lower-/.f64N/A
Applied rewrites39.6%
lift-/.f64N/A
lift--.f64N/A
sub-divN/A
frac-subN/A
*-commutativeN/A
lift-sqrt.f64N/A
lift-sqrt.f64N/A
rem-square-sqrtN/A
lower-/.f64N/A
Applied rewrites6.1%
Taylor expanded in x around -inf
unpow2N/A
rem-square-sqrtN/A
metadata-eval36.9
Applied rewrites36.9%
Taylor expanded in x around inf
lower-/.f64N/A
associate--l+N/A
+-commutativeN/A
unpow2N/A
associate-/r*N/A
metadata-evalN/A
associate-*r/N/A
associate-*r/N/A
metadata-evalN/A
div-subN/A
lower-+.f64N/A
lower-/.f64N/A
lower--.f64N/A
associate-*r/N/A
metadata-evalN/A
lower-/.f6498.9
Applied rewrites98.9%
Final simplification98.9%
(FPCore (x) :precision binary64 (/ (- (sqrt (/ 1.0 x))) (fma -2.0 x -1.5)))
double code(double x) {
return -sqrt((1.0 / x)) / fma(-2.0, x, -1.5);
}
function code(x) return Float64(Float64(-sqrt(Float64(1.0 / x))) / fma(-2.0, x, -1.5)) end
code[x_] := N[((-N[Sqrt[N[(1.0 / x), $MachinePrecision]], $MachinePrecision]) / N[(-2.0 * x + -1.5), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{-\sqrt{\frac{1}{x}}}{\mathsf{fma}\left(-2, x, -1.5\right)}
\end{array}
Initial program 39.5%
lift--.f64N/A
lift-/.f64N/A
lift-/.f64N/A
frac-subN/A
div-invN/A
metadata-evalN/A
div-invN/A
*-lft-identityN/A
flip--N/A
metadata-evalN/A
frac-timesN/A
frac-2negN/A
metadata-evalN/A
lift-/.f64N/A
associate-*r/N/A
Applied rewrites40.7%
Taylor expanded in x around 0
mul-1-negN/A
lower-neg.f64N/A
lower-sqrt.f64N/A
lower-/.f6499.3
Applied rewrites99.3%
lift-*.f64N/A
*-commutativeN/A
lift-+.f64N/A
+-commutativeN/A
distribute-rgt-inN/A
lower-fma.f64N/A
lift-+.f64N/A
+-commutativeN/A
lower-+.f64N/A
lift-+.f64N/A
+-commutativeN/A
lower-+.f64N/A
lower-*.f6499.3
lift-+.f64N/A
+-commutativeN/A
lower-+.f6499.3
Applied rewrites99.3%
Taylor expanded in x around inf
distribute-rgt-inN/A
distribute-rgt-inN/A
metadata-evalN/A
metadata-evalN/A
rem-square-sqrtN/A
unpow2N/A
*-commutativeN/A
associate-*l*N/A
lft-mult-inverseN/A
metadata-evalN/A
metadata-evalN/A
Applied rewrites98.6%
(FPCore (x) :precision binary64 (/ (/ 0.5 (+ 1.0 x)) (sqrt x)))
double code(double x) {
return (0.5 / (1.0 + x)) / sqrt(x);
}
real(8) function code(x)
real(8), intent (in) :: x
code = (0.5d0 / (1.0d0 + x)) / sqrt(x)
end function
public static double code(double x) {
return (0.5 / (1.0 + x)) / Math.sqrt(x);
}
def code(x): return (0.5 / (1.0 + x)) / math.sqrt(x)
function code(x) return Float64(Float64(0.5 / Float64(1.0 + x)) / sqrt(x)) end
function tmp = code(x) tmp = (0.5 / (1.0 + x)) / sqrt(x); end
code[x_] := N[(N[(0.5 / N[(1.0 + x), $MachinePrecision]), $MachinePrecision] / N[Sqrt[x], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{0.5}{1 + x}}{\sqrt{x}}
\end{array}
Initial program 39.5%
lift--.f64N/A
lift-/.f64N/A
clear-numN/A
lift-/.f64N/A
frac-subN/A
div-invN/A
metadata-evalN/A
*-rgt-identityN/A
*-commutativeN/A
associate-/r*N/A
lower-/.f64N/A
Applied rewrites39.6%
lift-/.f64N/A
lift--.f64N/A
sub-divN/A
frac-subN/A
*-commutativeN/A
lift-sqrt.f64N/A
lift-sqrt.f64N/A
rem-square-sqrtN/A
lower-/.f64N/A
Applied rewrites6.1%
Taylor expanded in x around inf
Applied rewrites97.8%
Final simplification97.8%
(FPCore (x) :precision binary64 (/ (/ 0.5 x) (sqrt x)))
double code(double x) {
return (0.5 / x) / sqrt(x);
}
real(8) function code(x)
real(8), intent (in) :: x
code = (0.5d0 / x) / sqrt(x)
end function
public static double code(double x) {
return (0.5 / x) / Math.sqrt(x);
}
def code(x): return (0.5 / x) / math.sqrt(x)
function code(x) return Float64(Float64(0.5 / x) / sqrt(x)) end
function tmp = code(x) tmp = (0.5 / x) / sqrt(x); end
code[x_] := N[(N[(0.5 / x), $MachinePrecision] / N[Sqrt[x], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{0.5}{x}}{\sqrt{x}}
\end{array}
Initial program 39.5%
lift--.f64N/A
lift-/.f64N/A
clear-numN/A
lift-/.f64N/A
frac-subN/A
div-invN/A
metadata-evalN/A
*-rgt-identityN/A
*-commutativeN/A
associate-/r*N/A
lower-/.f64N/A
Applied rewrites39.6%
Taylor expanded in x around inf
lower-/.f6497.7
Applied rewrites97.7%
(FPCore (x) :precision binary64 (/ (* 0.5 (sqrt x)) (* x x)))
double code(double x) {
return (0.5 * sqrt(x)) / (x * x);
}
real(8) function code(x)
real(8), intent (in) :: x
code = (0.5d0 * sqrt(x)) / (x * x)
end function
public static double code(double x) {
return (0.5 * Math.sqrt(x)) / (x * x);
}
def code(x): return (0.5 * math.sqrt(x)) / (x * x)
function code(x) return Float64(Float64(0.5 * sqrt(x)) / Float64(x * x)) end
function tmp = code(x) tmp = (0.5 * sqrt(x)) / (x * x); end
code[x_] := N[(N[(0.5 * N[Sqrt[x], $MachinePrecision]), $MachinePrecision] / N[(x * x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{0.5 \cdot \sqrt{x}}{x \cdot x}
\end{array}
Initial program 39.5%
Taylor expanded in x around inf
Applied rewrites83.7%
Taylor expanded in x around inf
Applied rewrites82.9%
(FPCore (x) :precision binary64 0.0)
double code(double x) {
return 0.0;
}
real(8) function code(x)
real(8), intent (in) :: x
code = 0.0d0
end function
public static double code(double x) {
return 0.0;
}
def code(x): return 0.0
function code(x) return 0.0 end
function tmp = code(x) tmp = 0.0; end
code[x_] := 0.0
\begin{array}{l}
\\
0
\end{array}
Initial program 39.5%
lift--.f64N/A
lift-/.f64N/A
clear-numN/A
lift-/.f64N/A
frac-subN/A
div-invN/A
metadata-evalN/A
*-rgt-identityN/A
*-commutativeN/A
associate-/r*N/A
lower-/.f64N/A
Applied rewrites39.6%
lift-/.f64N/A
lift--.f64N/A
sub-divN/A
frac-subN/A
*-commutativeN/A
lift-sqrt.f64N/A
lift-sqrt.f64N/A
rem-square-sqrtN/A
lower-/.f64N/A
Applied rewrites6.1%
Taylor expanded in x around -inf
unpow2N/A
rem-square-sqrtN/A
metadata-eval36.9
Applied rewrites36.9%
Taylor expanded in x around -inf
distribute-rgt-inN/A
unpow2N/A
rem-square-sqrtN/A
distribute-rgt-inN/A
metadata-evalN/A
mul0-rgt36.9
Applied rewrites36.9%
(FPCore (x) :precision binary64 (- (pow x -0.5) (pow (+ x 1.0) -0.5)))
double code(double x) {
return pow(x, -0.5) - pow((x + 1.0), -0.5);
}
real(8) function code(x)
real(8), intent (in) :: x
code = (x ** (-0.5d0)) - ((x + 1.0d0) ** (-0.5d0))
end function
public static double code(double x) {
return Math.pow(x, -0.5) - Math.pow((x + 1.0), -0.5);
}
def code(x): return math.pow(x, -0.5) - math.pow((x + 1.0), -0.5)
function code(x) return Float64((x ^ -0.5) - (Float64(x + 1.0) ^ -0.5)) end
function tmp = code(x) tmp = (x ^ -0.5) - ((x + 1.0) ^ -0.5); end
code[x_] := N[(N[Power[x, -0.5], $MachinePrecision] - N[Power[N[(x + 1.0), $MachinePrecision], -0.5], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
{x}^{-0.5} - {\left(x + 1\right)}^{-0.5}
\end{array}
herbie shell --seed 2024267
(FPCore (x)
:name "2isqrt (example 3.6)"
:precision binary64
:pre (and (> x 1.0) (< x 1e+308))
:alt
(! :herbie-platform default (- (pow x -1/2) (pow (+ x 1) -1/2)))
(- (/ 1.0 (sqrt x)) (/ 1.0 (sqrt (+ x 1.0)))))