Given's Rotation SVD example

Average Error: 13.6 → 6.6

Time: 8.5s

Precision: binary64

Cost: 27012

\[10^{-150} < \left|x\right| \land \left|x\right| < 10^{+150}\]

Math

\[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]

↓

\[\begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -1:\\ \;\;\;\;\frac{-p}{x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{0.5 \cdot \mathsf{fma}\left(\frac{1}{\mathsf{hypot}\left(x, p + p\right)}, x, 1\right)}\\ \end{array} \]

FPCore

(FPCore (p x)
 :precision binary64
 (sqrt (* 0.5 (+ 1.0 (/ x (sqrt (+ (* (* 4.0 p) p) (* x x))))))))

↓

(FPCore (p x)
 :precision binary64
 (if (<= (/ x (sqrt (+ (* p (* 4.0 p)) (* x x)))) -1.0)
   (/ (- p) x)
   (sqrt (* 0.5 (fma (/ 1.0 (hypot x (+ p p))) x 1.0)))))

C

double code(double p, double x) {
	return sqrt((0.5 * (1.0 + (x / sqrt((((4.0 * p) * p) + (x * x)))))));
}

↓

double code(double p, double x) {
	double tmp;
	if ((x / sqrt(((p * (4.0 * p)) + (x * x)))) <= -1.0) {
		tmp = -p / x;
	} else {
		tmp = sqrt((0.5 * fma((1.0 / hypot(x, (p + p))), x, 1.0)));
	}
	return tmp;
}

Julia

function code(p, x)
	return sqrt(Float64(0.5 * Float64(1.0 + Float64(x / sqrt(Float64(Float64(Float64(4.0 * p) * p) + Float64(x * x)))))))
end

↓

function code(p, x)
	tmp = 0.0
	if (Float64(x / sqrt(Float64(Float64(p * Float64(4.0 * p)) + Float64(x * x)))) <= -1.0)
		tmp = Float64(Float64(-p) / x);
	else
		tmp = sqrt(Float64(0.5 * fma(Float64(1.0 / hypot(x, Float64(p + p))), x, 1.0)));
	end
	return tmp
end

Wolfram

code[p_, x_] := N[Sqrt[N[(0.5 * N[(1.0 + N[(x / N[Sqrt[N[(N[(N[(4.0 * p), $MachinePrecision] * p), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]

↓

code[p_, x_] := If[LessEqual[N[(x / N[Sqrt[N[(N[(p * N[(4.0 * p), $MachinePrecision]), $MachinePrecision] + N[(x * x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], -1.0], N[((-p) / x), $MachinePrecision], N[Sqrt[N[(0.5 * N[(N[(1.0 / N[Sqrt[x ^ 2 + N[(p + p), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision] * x + 1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]]

Target

Original	13.6
Target	13.6
Herbie	6.6

\[\sqrt{0.5 + \frac{\mathsf{copysign}\left(0.5, x\right)}{\mathsf{hypot}\left(1, \frac{2 \cdot p}{x}\right)}} \]

Derivation

1. Split input into 2 regimes

2. if (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 4 p) p) (*.f64 x x)))) < -1

   1. Initial program 54.3

      \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]

   2. Taylor expanded in x around -inf 30.8

      \[\leadsto \sqrt{0.5 \cdot \color{blue}{\left(2 \cdot \frac{{p}^{2}}{{x}^{2}}\right)}} \]

   3. Taylor expanded in p around -inf 26.2

      \[\leadsto \color{blue}{-1 \cdot \frac{p}{x}} \]

   4. Simplified 26.2

      \[\leadsto \color{blue}{\frac{-p}{x}} \]
      Proof
      (/.f64 (neg.f64 p) x): 0 points increase in error, 0 points decrease in error
      (/.f64 (Rewrite<= mul-1-neg_binary64 (*.f64 -1 p)) x): 0 points increase in error, 0 points decrease in error
      (Rewrite<= associate-*r/_binary64 (*.f64 -1 (/.f64 p x))): 0 points increase in error, 0 points decrease in error

   if -1 < (/.f64 x (sqrt.f64 (+.f64 (*.f64 (*.f64 4 p) p) (*.f64 x x))))

   1. Initial program 0.2

      \[\sqrt{0.5 \cdot \left(1 + \frac{x}{\sqrt{\left(4 \cdot p\right) \cdot p + x \cdot x}}\right)} \]

   2. Applied egg-rr 0.2

      \[\leadsto \sqrt{0.5 \cdot \left(1 + \frac{x}{\color{blue}{\mathsf{hypot}\left(2 \cdot p, x\right)}}\right)} \]

   3. Applied egg-rr 0.2

      \[\leadsto \sqrt{0.5 \cdot \color{blue}{\mathsf{fma}\left(\frac{1}{\mathsf{hypot}\left(x, p + p\right)}, x, 1\right)}} \]
3. Recombined 2 regimes into one program.

4. Final simplification 6.6

   \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}} \leq -1:\\ \;\;\;\;\frac{-p}{x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{0.5 \cdot \mathsf{fma}\left(\frac{1}{\mathsf{hypot}\left(x, p + p\right)}, x, 1\right)}\\ \end{array} \]

Alternatives

Alternative 1
Error	6.6
Cost	20932

\[\begin{array}{l} t_0 := \frac{x}{\sqrt{p \cdot \left(4 \cdot p\right) + x \cdot x}}\\ \mathbf{if}\;t_0 \leq -1:\\ \;\;\;\;\frac{-p}{x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{0.5 \cdot \left(t_0 + 1\right)}\\ \end{array} \]

Alternative 2
Error	14.5
Cost	14096

\[\begin{array}{l} t_0 := \sqrt{0.5 \cdot \left(1 + x \cdot \frac{1}{\mathsf{hypot}\left(x, p \cdot 2\right)}\right)}\\ \mathbf{if}\;p \leq -1.0643312594750038 \cdot 10^{-67}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;p \leq -4.112956833155925 \cdot 10^{-198}:\\ \;\;\;\;\frac{p}{x}\\ \mathbf{elif}\;p \leq 2.378564407852842 \cdot 10^{-275}:\\ \;\;\;\;\sqrt{0.5 \cdot \left(1 + \frac{x}{\mathsf{hypot}\left(p \cdot 2, x\right)}\right)}\\ \mathbf{elif}\;p \leq 8.210755767189288 \cdot 10^{-116}:\\ \;\;\;\;\frac{-p}{x}\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 3
Error	14.5
Cost	13968

\[\begin{array}{l} t_0 := \sqrt{0.5 \cdot \left(1 + \frac{x}{\mathsf{hypot}\left(p \cdot 2, x\right)}\right)}\\ \mathbf{if}\;p \leq -1.0643312594750038 \cdot 10^{-67}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;p \leq -4.112956833155925 \cdot 10^{-198}:\\ \;\;\;\;\frac{p}{x}\\ \mathbf{elif}\;p \leq 2.378564407852842 \cdot 10^{-275}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;p \leq 8.210755767189288 \cdot 10^{-116}:\\ \;\;\;\;\frac{-p}{x}\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 4
Error	20.0
Cost	6992

\[\begin{array}{l} \mathbf{if}\;p \leq -1.0643312594750038 \cdot 10^{-67}:\\ \;\;\;\;\sqrt{0.5}\\ \mathbf{elif}\;p \leq -3.135717507482701 \cdot 10^{-274}:\\ \;\;\;\;\frac{p}{x}\\ \mathbf{elif}\;p \leq 2.378564407852842 \cdot 10^{-275}:\\ \;\;\;\;1\\ \mathbf{elif}\;p \leq 1.2335977965435276 \cdot 10^{-25}:\\ \;\;\;\;\frac{-p}{x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{0.5}\\ \end{array} \]

Alternative 5
Error	20.4
Cost	6860

\[\begin{array}{l} \mathbf{if}\;p \leq -1.0643312594750038 \cdot 10^{-67}:\\ \;\;\;\;\sqrt{0.5}\\ \mathbf{elif}\;p \leq -1.8011479606934947 \cdot 10^{-295}:\\ \;\;\;\;\frac{p}{x}\\ \mathbf{elif}\;p \leq 1.2335977965435276 \cdot 10^{-25}:\\ \;\;\;\;\frac{-p}{x}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{0.5}\\ \end{array} \]

Alternative 6
Error	46.8
Cost	388

\[\begin{array}{l} \mathbf{if}\;p \leq -1.8011479606934947 \cdot 10^{-295}:\\ \;\;\;\;\frac{p}{x}\\ \mathbf{else}:\\ \;\;\;\;\frac{-p}{x}\\ \end{array} \]

Alternative 7
Error	53.7
Cost	192

\[\frac{p}{x} \]

Alternative 8
Error	60.1
Cost	64

\[0 \]

Reproduce

herbie shell --seed 2022317 
(FPCore (p x)
  :name "Given's Rotation SVD example"
  :precision binary64
  :pre (and (< 1e-150 (fabs x)) (< (fabs x) 1e+150))

  :herbie-target
  (sqrt (+ 0.5 (/ (copysign 0.5 x) (hypot 1.0 (/ (* 2.0 p) x)))))

  (sqrt (* 0.5 (+ 1.0 (/ x (sqrt (+ (* (* 4.0 p) p) (* x x))))))))