Average Error: 1.8 → 1.8
Time: 8.0s
Precision: binary64
\[\frac{a \cdot {k}^{m}}{\left(1 + 10 \cdot k\right) + k \cdot k} \]
↓
\[\begin{array}{l} t_0 := \sqrt{\mathsf{fma}\left(k, k + 10, 1\right)}\\ \frac{a}{t_0} \cdot \frac{{k}^{m}}{t_0} \end{array} \]
\frac{a \cdot {k}^{m}}{\left(1 + 10 \cdot k\right) + k \cdot k}
↓
\begin{array}{l}
t_0 := \sqrt{\mathsf{fma}\left(k, k + 10, 1\right)}\\
\frac{a}{t_0} \cdot \frac{{k}^{m}}{t_0}
\end{array}

(FPCore (a k m)
 :precision binary64
 (/ (* a (pow k m)) (+ (+ 1.0 (* 10.0 k)) (* k k))))
↓
(FPCore (a k m)
 :precision binary64
 (let* ((t_0 (sqrt (fma k (+ k 10.0) 1.0)))) (* (/ a t_0) (/ (pow k m) t_0))))
double code(double a, double k, double m) {
	return (a * pow(k, m)) / ((1.0 + (10.0 * k)) + (k * k));
}
↓
double code(double a, double k, double m) {
	double t_0 = sqrt(fma(k, (k + 10.0), 1.0));
	return (a / t_0) * (pow(k, m) / t_0);
}

Error

Bits error versus a

Bits error versus k

Bits error versus m

Derivation

  1. Initial program 1.8

    \[\frac{a \cdot {k}^{m}}{\left(1 + 10 \cdot k\right) + k \cdot k} \]

  2. Simplified1.8

    \[\leadsto \color{blue}{\frac{a \cdot {k}^{m}}{\mathsf{fma}\left(k, k + 10, 1\right)}} \]

  3. Applied add-sqr-sqrt_binary641.8

    \[\leadsto \frac{a \cdot {k}^{m}}{\color{blue}{\sqrt{\mathsf{fma}\left(k, k + 10, 1\right)} \cdot \sqrt{\mathsf{fma}\left(k, k + 10, 1\right)}}} \]

  4. Applied times-frac_binary641.8

    \[\leadsto \color{blue}{\frac{a}{\sqrt{\mathsf{fma}\left(k, k + 10, 1\right)}} \cdot \frac{{k}^{m}}{\sqrt{\mathsf{fma}\left(k, k + 10, 1\right)}}} \]

  5. Final simplification1.8

    \[\leadsto \frac{a}{\sqrt{\mathsf{fma}\left(k, k + 10, 1\right)}} \cdot \frac{{k}^{m}}{\sqrt{\mathsf{fma}\left(k, k + 10, 1\right)}} \]

Reproduce

herbie shell --seed 2021275 
(FPCore (a k m)
  :name "Falkner and Boettcher, Appendix A"
  :precision binary64
  (/ (* a (pow k m)) (+ (+ 1.0 (* 10.0 k)) (* k k))))