bug323 (missed optimization)

Percentage Accurate: 6.9% → 10.5%
Time: 7.9s
Alternatives: 6
Speedup: 1.0×

Specification

?
\[0 \leq x \land x \leq 0.5\]
\[\begin{array}{l} \\ \cos^{-1} \left(1 - x\right) \end{array} \]
(FPCore (x) :precision binary64 (acos (- 1.0 x)))
double code(double x) {
	return acos((1.0 - x));
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = acos((1.0d0 - x))
end function
public static double code(double x) {
	return Math.acos((1.0 - x));
}
def code(x):
	return math.acos((1.0 - x))
function code(x)
	return acos(Float64(1.0 - x))
end
function tmp = code(x)
	tmp = acos((1.0 - x));
end
code[x_] := N[ArcCos[N[(1.0 - x), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}

\\
\cos^{-1} \left(1 - x\right)
\end{array}

Sampling outcomes in binary64 precision:

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 6 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: 6.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \cos^{-1} \left(1 - x\right) \end{array} \]
(FPCore (x) :precision binary64 (acos (- 1.0 x)))
double code(double x) {
	return acos((1.0 - x));
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = acos((1.0d0 - x))
end function
public static double code(double x) {
	return Math.acos((1.0 - x));
}
def code(x):
	return math.acos((1.0 - x))
function code(x)
	return acos(Float64(1.0 - x))
end
function tmp = code(x)
	tmp = acos((1.0 - x));
end
code[x_] := N[ArcCos[N[(1.0 - x), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}

\\
\cos^{-1} \left(1 - x\right)
\end{array}

Alternative 1: 10.5% accurate, 0.4× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left({\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right)}^{0.25}, 0.5 \cdot \sqrt{\mathsf{PI}\left(\right)}, -\sin^{-1} \left(1 - x\right)\right) \end{array} \]
(FPCore (x)
 :precision binary64
 (fma (pow (* (PI) (PI)) 0.25) (* 0.5 (sqrt (PI))) (- (asin (- 1.0 x)))))
\begin{array}{l}

\\
\mathsf{fma}\left({\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right)}^{0.25}, 0.5 \cdot \sqrt{\mathsf{PI}\left(\right)}, -\sin^{-1} \left(1 - x\right)\right)
\end{array}
Derivation
  1. Initial program 7.8%

    \[\cos^{-1} \left(1 - x\right) \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-acos.f64N/A

      \[\leadsto \color{blue}{\cos^{-1} \left(1 - x\right)} \]
    2. acos-asinN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} - \sin^{-1} \left(1 - x\right)} \]
    3. sub-negN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right)} \]
    4. div-invN/A

      \[\leadsto \color{blue}{\mathsf{PI}\left(\right) \cdot \frac{1}{2}} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    5. add-sqr-sqrtN/A

      \[\leadsto \color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \sqrt{\mathsf{PI}\left(\right)}\right)} \cdot \frac{1}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    6. associate-*l*N/A

      \[\leadsto \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    7. lower-fma.f64N/A

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right)} \]
    8. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    9. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\color{blue}{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    10. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    11. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    12. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\color{blue}{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    13. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    14. lower-neg.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \color{blue}{-\sin^{-1} \left(1 - x\right)}\right) \]
    15. lower-asin.f646.0

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, -\color{blue}{\sin^{-1} \left(1 - x\right)}\right) \]
  4. Applied rewrites6.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, -\sin^{-1} \left(1 - x\right)\right)} \]
  5. Step-by-step derivation
    1. lift-sqrt.f64N/A

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

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

      \[\leadsto \mathsf{fma}\left({\mathsf{PI}\left(\right)}^{\color{blue}{\left(\frac{1}{4} + \frac{1}{4}\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\sin^{-1} \left(1 - x\right)\right) \]
    4. pow-prod-upN/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{{\mathsf{PI}\left(\right)}^{\frac{1}{4}} \cdot {\mathsf{PI}\left(\right)}^{\frac{1}{4}}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\sin^{-1} \left(1 - x\right)\right) \]
    5. pow-prod-downN/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{{\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right)}^{\frac{1}{4}}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\sin^{-1} \left(1 - x\right)\right) \]
    6. lift-*.f64N/A

      \[\leadsto \mathsf{fma}\left({\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right)}}^{\frac{1}{4}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\sin^{-1} \left(1 - x\right)\right) \]
    7. lower-pow.f6411.3

      \[\leadsto \mathsf{fma}\left(\color{blue}{{\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right)}^{0.25}}, \sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, -\sin^{-1} \left(1 - x\right)\right) \]
  6. Applied rewrites11.3%

    \[\leadsto \mathsf{fma}\left(\color{blue}{{\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right)}^{0.25}}, \sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, -\sin^{-1} \left(1 - x\right)\right) \]
  7. Final simplification11.3%

    \[\leadsto \mathsf{fma}\left({\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right)}^{0.25}, 0.5 \cdot \sqrt{\mathsf{PI}\left(\right)}, -\sin^{-1} \left(1 - x\right)\right) \]
  8. Add Preprocessing

Alternative 2: 9.5% accurate, 0.5× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \cos^{-1} \left(1 - x\right)\\ \mathbf{if}\;t\_0 \leq 0:\\ \;\;\;\;\cos^{-1} \left(-x\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (let* ((t_0 (acos (- 1.0 x)))) (if (<= t_0 0.0) (acos (- x)) t_0)))
double code(double x) {
	double t_0 = acos((1.0 - x));
	double tmp;
	if (t_0 <= 0.0) {
		tmp = acos(-x);
	} else {
		tmp = t_0;
	}
	return tmp;
}
real(8) function code(x)
    real(8), intent (in) :: x
    real(8) :: t_0
    real(8) :: tmp
    t_0 = acos((1.0d0 - x))
    if (t_0 <= 0.0d0) then
        tmp = acos(-x)
    else
        tmp = t_0
    end if
    code = tmp
end function
public static double code(double x) {
	double t_0 = Math.acos((1.0 - x));
	double tmp;
	if (t_0 <= 0.0) {
		tmp = Math.acos(-x);
	} else {
		tmp = t_0;
	}
	return tmp;
}
def code(x):
	t_0 = math.acos((1.0 - x))
	tmp = 0
	if t_0 <= 0.0:
		tmp = math.acos(-x)
	else:
		tmp = t_0
	return tmp
function code(x)
	t_0 = acos(Float64(1.0 - x))
	tmp = 0.0
	if (t_0 <= 0.0)
		tmp = acos(Float64(-x));
	else
		tmp = t_0;
	end
	return tmp
end
function tmp_2 = code(x)
	t_0 = acos((1.0 - x));
	tmp = 0.0;
	if (t_0 <= 0.0)
		tmp = acos(-x);
	else
		tmp = t_0;
	end
	tmp_2 = tmp;
end
code[x_] := Block[{t$95$0 = N[ArcCos[N[(1.0 - x), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$0, 0.0], N[ArcCos[(-x)], $MachinePrecision], t$95$0]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \cos^{-1} \left(1 - x\right)\\
\mathbf{if}\;t\_0 \leq 0:\\
\;\;\;\;\cos^{-1} \left(-x\right)\\

\mathbf{else}:\\
\;\;\;\;t\_0\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (acos.f64 (-.f64 #s(literal 1 binary64) x)) < 0.0

    1. Initial program 3.9%

      \[\cos^{-1} \left(1 - x\right) \]
    2. Add Preprocessing
    3. Taylor expanded in x around inf

      \[\leadsto \cos^{-1} \color{blue}{\left(-1 \cdot x\right)} \]
    4. Step-by-step derivation
      1. mul-1-negN/A

        \[\leadsto \cos^{-1} \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]
      2. lower-neg.f646.6

        \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
    5. Applied rewrites6.6%

      \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]

    if 0.0 < (acos.f64 (-.f64 #s(literal 1 binary64) x))

    1. Initial program 56.9%

      \[\cos^{-1} \left(1 - x\right) \]
    2. Add Preprocessing
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 3: 10.4% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\mathsf{PI}\left(\right)}\\ t_1 := 0.5 \cdot t\_0\\ \mathsf{fma}\left(t\_0, t\_1, -\mathsf{fma}\left(t\_1, t\_0, -\cos^{-1} \left(1 - x\right)\right)\right) \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (let* ((t_0 (sqrt (PI))) (t_1 (* 0.5 t_0)))
   (fma t_0 t_1 (- (fma t_1 t_0 (- (acos (- 1.0 x))))))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sqrt{\mathsf{PI}\left(\right)}\\
t_1 := 0.5 \cdot t\_0\\
\mathsf{fma}\left(t\_0, t\_1, -\mathsf{fma}\left(t\_1, t\_0, -\cos^{-1} \left(1 - x\right)\right)\right)
\end{array}
\end{array}
Derivation
  1. Initial program 7.8%

    \[\cos^{-1} \left(1 - x\right) \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-acos.f64N/A

      \[\leadsto \color{blue}{\cos^{-1} \left(1 - x\right)} \]
    2. acos-asinN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} - \sin^{-1} \left(1 - x\right)} \]
    3. sub-negN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right)} \]
    4. div-invN/A

      \[\leadsto \color{blue}{\mathsf{PI}\left(\right) \cdot \frac{1}{2}} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    5. add-sqr-sqrtN/A

      \[\leadsto \color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \sqrt{\mathsf{PI}\left(\right)}\right)} \cdot \frac{1}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    6. associate-*l*N/A

      \[\leadsto \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    7. lower-fma.f64N/A

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right)} \]
    8. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    9. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\color{blue}{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    10. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    11. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    12. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\color{blue}{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    13. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    14. lower-neg.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \color{blue}{-\sin^{-1} \left(1 - x\right)}\right) \]
    15. lower-asin.f646.0

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, -\color{blue}{\sin^{-1} \left(1 - x\right)}\right) \]
  4. Applied rewrites6.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, -\sin^{-1} \left(1 - x\right)\right)} \]
  5. Step-by-step derivation
    1. lift-asin.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\color{blue}{\sin^{-1} \left(1 - x\right)}\right) \]
    2. asin-acosN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\color{blue}{\left(\frac{\mathsf{PI}\left(\right)}{2} - \cos^{-1} \left(1 - x\right)\right)}\right) \]
    3. lift-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\frac{\color{blue}{\mathsf{PI}\left(\right)}}{2} - \cos^{-1} \left(1 - x\right)\right)\right) \]
    4. div-invN/A

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

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\mathsf{PI}\left(\right) \cdot \color{blue}{\frac{1}{2}} - \cos^{-1} \left(1 - x\right)\right)\right) \]
    6. *-commutativeN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\color{blue}{\frac{1}{2} \cdot \mathsf{PI}\left(\right)} - \cos^{-1} \left(1 - x\right)\right)\right) \]
    7. lift-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\color{blue}{\frac{1}{2} \cdot \mathsf{PI}\left(\right)} - \cos^{-1} \left(1 - x\right)\right)\right) \]
    8. lift-acos.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) - \color{blue}{\cos^{-1} \left(1 - x\right)}\right)\right) \]
    9. sub-negN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\color{blue}{\left(\frac{1}{2} \cdot \mathsf{PI}\left(\right) + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)}\right) \]
    10. lift-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\color{blue}{\frac{1}{2} \cdot \mathsf{PI}\left(\right)} + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    11. rem-square-sqrtN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\frac{1}{2} \cdot \color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \sqrt{\mathsf{PI}\left(\right)}\right)} + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    12. lift-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\frac{1}{2} \cdot \left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)}} \cdot \sqrt{\mathsf{PI}\left(\right)}\right) + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    13. lift-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\frac{1}{2} \cdot \left(\sqrt{\mathsf{PI}\left(\right)} \cdot \color{blue}{\sqrt{\mathsf{PI}\left(\right)}}\right) + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    14. associate-*r*N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\color{blue}{\left(\frac{1}{2} \cdot \sqrt{\mathsf{PI}\left(\right)}\right) \cdot \sqrt{\mathsf{PI}\left(\right)}} + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    15. *-commutativeN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} \cdot \sqrt{\mathsf{PI}\left(\right)} + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    16. lift-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\left(\color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} \cdot \sqrt{\mathsf{PI}\left(\right)} + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    17. lower-fma.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, -\color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \sqrt{\mathsf{PI}\left(\right)}, \mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)}\right) \]
    18. lower-neg.f6411.3

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, -\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, \sqrt{\mathsf{PI}\left(\right)}, \color{blue}{-\cos^{-1} \left(1 - x\right)}\right)\right) \]
  6. Applied rewrites11.3%

    \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, -\color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)} \cdot 0.5, \sqrt{\mathsf{PI}\left(\right)}, -\cos^{-1} \left(1 - x\right)\right)}\right) \]
  7. Final simplification11.3%

    \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, 0.5 \cdot \sqrt{\mathsf{PI}\left(\right)}, -\mathsf{fma}\left(0.5 \cdot \sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)}, -\cos^{-1} \left(1 - x\right)\right)\right) \]
  8. Add Preprocessing

Alternative 4: 9.5% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 5.5 \cdot 10^{-17}:\\ \;\;\;\;\cos^{-1} \left(-x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -\sin^{-1} \left(1 - x\right)\right)\\ \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (if (<= x 5.5e-17) (acos (- x)) (fma (PI) 0.5 (- (asin (- 1.0 x))))))
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 5.5 \cdot 10^{-17}:\\
\;\;\;\;\cos^{-1} \left(-x\right)\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -\sin^{-1} \left(1 - x\right)\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < 5.50000000000000001e-17

    1. Initial program 3.9%

      \[\cos^{-1} \left(1 - x\right) \]
    2. Add Preprocessing
    3. Taylor expanded in x around inf

      \[\leadsto \cos^{-1} \color{blue}{\left(-1 \cdot x\right)} \]
    4. Step-by-step derivation
      1. mul-1-negN/A

        \[\leadsto \cos^{-1} \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]
      2. lower-neg.f646.6

        \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
    5. Applied rewrites6.6%

      \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]

    if 5.50000000000000001e-17 < x

    1. Initial program 56.9%

      \[\cos^{-1} \left(1 - x\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-acos.f64N/A

        \[\leadsto \color{blue}{\cos^{-1} \left(1 - x\right)} \]
      2. acos-asinN/A

        \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} - \sin^{-1} \left(1 - x\right)} \]
      3. sub-negN/A

        \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right)} \]
      4. div-invN/A

        \[\leadsto \color{blue}{\mathsf{PI}\left(\right) \cdot \frac{1}{2}} + \left(\mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
      5. lower-fma.f64N/A

        \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{PI}\left(\right), \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right)} \]
      6. lower-PI.f64N/A

        \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{PI}\left(\right)}, \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
      7. metadata-evalN/A

        \[\leadsto \mathsf{fma}\left(\mathsf{PI}\left(\right), \color{blue}{\frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
      8. lower-neg.f64N/A

        \[\leadsto \mathsf{fma}\left(\mathsf{PI}\left(\right), \frac{1}{2}, \color{blue}{-\sin^{-1} \left(1 - x\right)}\right) \]
      9. lower-asin.f6457.1

        \[\leadsto \mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -\color{blue}{\sin^{-1} \left(1 - x\right)}\right) \]
    4. Applied rewrites57.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{PI}\left(\right), 0.5, -\sin^{-1} \left(1 - x\right)\right)} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 5: 6.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \cos^{-1} \left(-x\right) \end{array} \]
(FPCore (x) :precision binary64 (acos (- x)))
double code(double x) {
	return acos(-x);
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = acos(-x)
end function
public static double code(double x) {
	return Math.acos(-x);
}
def code(x):
	return math.acos(-x)
function code(x)
	return acos(Float64(-x))
end
function tmp = code(x)
	tmp = acos(-x);
end
code[x_] := N[ArcCos[(-x)], $MachinePrecision]
\begin{array}{l}

\\
\cos^{-1} \left(-x\right)
\end{array}
Derivation
  1. Initial program 7.8%

    \[\cos^{-1} \left(1 - x\right) \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \cos^{-1} \color{blue}{\left(-1 \cdot x\right)} \]
  4. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto \cos^{-1} \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]
    2. lower-neg.f647.0

      \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
  5. Applied rewrites7.0%

    \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
  6. Add Preprocessing

Alternative 6: 3.8% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \cos^{-1} 1 \end{array} \]
(FPCore (x) :precision binary64 (acos 1.0))
double code(double x) {
	return acos(1.0);
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = acos(1.0d0)
end function
public static double code(double x) {
	return Math.acos(1.0);
}
def code(x):
	return math.acos(1.0)
function code(x)
	return acos(1.0)
end
function tmp = code(x)
	tmp = acos(1.0);
end
code[x_] := N[ArcCos[1.0], $MachinePrecision]
\begin{array}{l}

\\
\cos^{-1} 1
\end{array}
Derivation
  1. Initial program 7.8%

    \[\cos^{-1} \left(1 - x\right) \]
  2. Add Preprocessing
  3. Taylor expanded in x around 0

    \[\leadsto \cos^{-1} \color{blue}{1} \]
  4. Step-by-step derivation
    1. Applied rewrites3.8%

      \[\leadsto \cos^{-1} \color{blue}{1} \]
    2. Add Preprocessing

    Developer Target 1: 100.0% accurate, 0.8× speedup?

    \[\begin{array}{l} \\ 2 \cdot \sin^{-1} \left(\sqrt{\frac{x}{2}}\right) \end{array} \]
    (FPCore (x) :precision binary64 (* 2.0 (asin (sqrt (/ x 2.0)))))
    double code(double x) {
    	return 2.0 * asin(sqrt((x / 2.0)));
    }
    
    real(8) function code(x)
        real(8), intent (in) :: x
        code = 2.0d0 * asin(sqrt((x / 2.0d0)))
    end function
    
    public static double code(double x) {
    	return 2.0 * Math.asin(Math.sqrt((x / 2.0)));
    }
    
    def code(x):
    	return 2.0 * math.asin(math.sqrt((x / 2.0)))
    
    function code(x)
    	return Float64(2.0 * asin(sqrt(Float64(x / 2.0))))
    end
    
    function tmp = code(x)
    	tmp = 2.0 * asin(sqrt((x / 2.0)));
    end
    
    code[x_] := N[(2.0 * N[ArcSin[N[Sqrt[N[(x / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
    
    \begin{array}{l}
    
    \\
    2 \cdot \sin^{-1} \left(\sqrt{\frac{x}{2}}\right)
    \end{array}
    

    Reproduce

    ?
    herbie shell --seed 2024327 
    (FPCore (x)
      :name "bug323 (missed optimization)"
      :precision binary64
      :pre (and (<= 0.0 x) (<= x 0.5))
    
      :alt
      (! :herbie-platform default (* 2 (asin (sqrt (/ x 2)))))
    
      (acos (- 1.0 x)))