_multiplyComplex, imaginary part

Average Accuracy: 77.1% → 77.1%

Time: 2.3s

Precision: binary64

Cost: 6720

Math

\[x.re \cdot y.im + x.im \cdot y.re \]

↓

\[\mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right) \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (+ (* x.re y.im) (* x.im y.re)))

↓

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (fma x.re y.im (* x.im y.re)))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return (x_46_re * y_46_im) + (x_46_im * y_46_re);
}

↓

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return fma(x_46_re, y_46_im, (x_46_im * y_46_re));
}

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	return Float64(Float64(x_46_re * y_46_im) + Float64(x_46_im * y_46_re))
end

↓

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	return fma(x_46_re, y_46_im, Float64(x_46_im * y_46_re))
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := N[(N[(x$46$re * y$46$im), $MachinePrecision] + N[(x$46$im * y$46$re), $MachinePrecision]), $MachinePrecision]

↓

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := N[(x$46$re * y$46$im + N[(x$46$im * y$46$re), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 78.1%

   \[x.re \cdot y.im + x.im \cdot y.re \]

2. Simplified 78.1%

   \[\leadsto \color{blue}{\mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right)} \]
   Proof

   [Start] 78.1	\[ x.re \cdot y.im + x.im \cdot y.re \]
   fma-def [=>] 78.1	\[ \color{blue}{\mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right)} \]

3. Final simplification 78.1%

   \[\leadsto \mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right) \]

Alternatives

Alternative 1
Accuracy	51.0%
Cost	721

\[\begin{array}{l} \mathbf{if}\;y.im \leq -2.2 \cdot 10^{-151}:\\ \;\;\;\;x.re \cdot y.im\\ \mathbf{elif}\;y.im \leq 7.6 \cdot 10^{-30} \lor \neg \left(y.im \leq 2.5 \cdot 10^{+29}\right) \land y.im \leq 1.42 \cdot 10^{+51}:\\ \;\;\;\;x.im \cdot y.re\\ \mathbf{else}:\\ \;\;\;\;x.re \cdot y.im\\ \end{array} \]

Alternative 2
Accuracy	77.1%
Cost	448

\[x.re \cdot y.im + x.im \cdot y.re \]

Alternative 3
Accuracy	41.3%
Cost	192

\[x.re \cdot y.im \]

Reproduce

herbie shell --seed 2023157 
(FPCore (x.re x.im y.re y.im)
  :name "_multiplyComplex, imaginary part"
  :precision binary64
  (+ (* x.re y.im) (* x.im y.re)))