Average Error: 0.0 → 0.0
Time: 9.2s
Precision: 64
\[500 \cdot \left(x - y\right)\]
\[\mathsf{fma}\left(500, x, \left(-y\right) \cdot 500\right)\]
500 \cdot \left(x - y\right)
\mathsf{fma}\left(500, x, \left(-y\right) \cdot 500\right)
double f(double x, double y) {
        double r223663 = 500.0;
        double r223664 = x;
        double r223665 = y;
        double r223666 = r223664 - r223665;
        double r223667 = r223663 * r223666;
        return r223667;
}

double f(double x, double y) {
        double r223668 = 500.0;
        double r223669 = x;
        double r223670 = y;
        double r223671 = -r223670;
        double r223672 = r223671 * r223668;
        double r223673 = fma(r223668, r223669, r223672);
        return r223673;
}

Error

Bits error versus x

Bits error versus y

Derivation

  1. Initial program 0.0

    \[500 \cdot \left(x - y\right)\]
  2. Using strategy rm
  3. Applied sub-neg0.0

    \[\leadsto 500 \cdot \color{blue}{\left(x + \left(-y\right)\right)}\]
  4. Applied distribute-lft-in0.0

    \[\leadsto \color{blue}{500 \cdot x + 500 \cdot \left(-y\right)}\]
  5. Simplified0.0

    \[\leadsto 500 \cdot x + \color{blue}{\left(-y\right) \cdot 500}\]
  6. Using strategy rm
  7. Applied fma-def0.0

    \[\leadsto \color{blue}{\mathsf{fma}\left(500, x, \left(-y\right) \cdot 500\right)}\]
  8. Final simplification0.0

    \[\leadsto \mathsf{fma}\left(500, x, \left(-y\right) \cdot 500\right)\]

Reproduce

herbie shell --seed 2019326 +o rules:numerics
(FPCore (x y)
  :name "Data.Colour.CIE:cieLABView from colour-2.3.3, B"
  :precision binary64
  (* 500 (- x y)))