Average Error: 61.8 → 0.3
Time: 14.1s
Precision: 64
\[0.900000000000000022 \le t \le 1.1000000000000001\]
\[\left(1 + t \cdot 2 \cdot 10^{-16}\right) \cdot \left(1 + t \cdot 2 \cdot 10^{-16}\right) + \left(-1 - 2 \cdot \left(t \cdot 2 \cdot 10^{-16}\right)\right)\]
↓
\[\left(t \cdot 3.9999999999999997 \cdot 10^{-32}\right) \cdot {t}^{\left(\frac{2}{2}\right)}\]
\left(1 + t \cdot 2 \cdot 10^{-16}\right) \cdot \left(1 + t \cdot 2 \cdot 10^{-16}\right) + \left(-1 - 2 \cdot \left(t \cdot 2 \cdot 10^{-16}\right)\right)
↓
\left(t \cdot 3.9999999999999997 \cdot 10^{-32}\right) \cdot {t}^{\left(\frac{2}{2}\right)}
double f(double t) {
        double r68921 = 1.0;
        double r68922 = t;
        double r68923 = 2e-16;
        double r68924 = r68922 * r68923;
        double r68925 = r68921 + r68924;
        double r68926 = r68925 * r68925;
        double r68927 = -1.0;
        double r68928 = 2.0;
        double r68929 = r68928 * r68924;
        double r68930 = r68927 - r68929;
        double r68931 = r68926 + r68930;
        return r68931;
}
↓
double f(double t) {
        double r68932 = t;
        double r68933 = 3.9999999999999997e-32;
        double r68934 = r68932 * r68933;
        double r68935 = 2.0;
        double r68936 = r68935 / r68935;
        double r68937 = pow(r68932, r68936);
        double r68938 = r68934 * r68937;
        return r68938;
}

Error

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original61.8
Target50.6
Herbie0.3
\[\mathsf{fma}\left(1 + t \cdot 2 \cdot 10^{-16}, 1 + t \cdot 2 \cdot 10^{-16}, -1 - 2 \cdot \left(t \cdot 2 \cdot 10^{-16}\right)\right)\]

Derivation

  1. Initial program 61.8

    \[\left(1 + t \cdot 2 \cdot 10^{-16}\right) \cdot \left(1 + t \cdot 2 \cdot 10^{-16}\right) + \left(-1 - 2 \cdot \left(t \cdot 2 \cdot 10^{-16}\right)\right)\]

  2. Taylor expanded around 0 0.3

    \[\leadsto \color{blue}{3.9999999999999997 \cdot 10^{-32} \cdot {t}^{2}}\]
  3. Using strategy rm

  4. Applied sqr-pow0.3

    \[\leadsto 3.9999999999999997 \cdot 10^{-32} \cdot \color{blue}{\left({t}^{\left(\frac{2}{2}\right)} \cdot {t}^{\left(\frac{2}{2}\right)}\right)}\]

  5. Applied associate-*r*0.3

    \[\leadsto \color{blue}{\left(3.9999999999999997 \cdot 10^{-32} \cdot {t}^{\left(\frac{2}{2}\right)}\right) \cdot {t}^{\left(\frac{2}{2}\right)}}\]

  6. Simplified0.3

    \[\leadsto \color{blue}{\left(t \cdot 3.9999999999999997 \cdot 10^{-32}\right)} \cdot {t}^{\left(\frac{2}{2}\right)}\]

  7. Final simplification0.3

    \[\leadsto \left(t \cdot 3.9999999999999997 \cdot 10^{-32}\right) \cdot {t}^{\left(\frac{2}{2}\right)}\]

Reproduce

herbie shell --seed 2020045 
(FPCore (t)
  :name "fma_test1"
  :precision binary64
  :pre (<= 0.9 t 1.1)

  :herbie-target
  (fma (+ 1 (* t 2e-16)) (+ 1 (* t 2e-16)) (- -1 (* 2 (* t 2e-16))))

  (+ (* (+ 1 (* t 2e-16)) (+ 1 (* t 2e-16))) (- -1 (* 2 (* t 2e-16)))))