Average Error: 12.3 → 0.6
Time: 1.3m
Precision: 64
Internal Precision: 576
\[\left(\left(3 + \frac{2}{r \cdot r}\right) - \frac{\left(0.125 \cdot \left(3 - 2 \cdot v\right)\right) \cdot \left(\left(\left(w \cdot w\right) \cdot r\right) \cdot r\right)}{1 - v}\right) - 4.5\]
\[(\left(\frac{(-2 \cdot v + 3)_*}{1 - v} \cdot 0.125\right) \cdot \left(\left(-w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\frac{\frac{\left(9 - 4.5 \cdot 4.5\right) \cdot (\left(3 - 4.5\right) \cdot r + \left(\frac{2}{r}\right))_*}{4.5 + -3}}{r \cdot \left(-3 - 4.5\right)}\right))_*\]

Error

Bits error versus v

Bits error versus w

Bits error versus r

Derivation

  1. Initial program 12.3

    \[\left(\left(3 + \frac{2}{r \cdot r}\right) - \frac{\left(0.125 \cdot \left(3 - 2 \cdot v\right)\right) \cdot \left(\left(\left(w \cdot w\right) \cdot r\right) \cdot r\right)}{1 - v}\right) - 4.5\]
  2. Initial simplification0.4

    \[\leadsto \left(3 + \frac{2}{r \cdot r}\right) - (\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*\]
  3. Using strategy rm
  4. Applied add-sqr-sqrt1.0

    \[\leadsto \left(3 + \frac{2}{r \cdot r}\right) - \color{blue}{\sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*} \cdot \sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}}\]
  5. Applied *-un-lft-identity1.0

    \[\leadsto \color{blue}{1 \cdot \left(3 + \frac{2}{r \cdot r}\right)} - \sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*} \cdot \sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}\]
  6. Applied prod-diff1.0

    \[\leadsto \color{blue}{(1 \cdot \left(3 + \frac{2}{r \cdot r}\right) + \left(-\sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*} \cdot \sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}\right))_* + (\left(-\sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}\right) \cdot \left(\sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}\right) + \left(\sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*} \cdot \sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}\right))_*}\]
  7. Simplified0.4

    \[\leadsto \color{blue}{(\left(0.125 \cdot \frac{(-2 \cdot v + 3)_*}{1 - v}\right) \cdot \left(-\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\left(\left(-4.5\right) + 3\right) + \frac{\frac{2}{r}}{r}\right))_*} + (\left(-\sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}\right) \cdot \left(\sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}\right) + \left(\sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*} \cdot \sqrt{(\left(\frac{(-2 \cdot v + 3)_*}{\frac{1 - v}{0.125}}\right) \cdot \left(\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + 4.5)_*}\right))_*\]
  8. Simplified0.3

    \[\leadsto (\left(0.125 \cdot \frac{(-2 \cdot v + 3)_*}{1 - v}\right) \cdot \left(-\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\left(\left(-4.5\right) + 3\right) + \frac{\frac{2}{r}}{r}\right))_* + \color{blue}{0}\]
  9. Using strategy rm
  10. Applied flip-+0.3

    \[\leadsto (\left(0.125 \cdot \frac{(-2 \cdot v + 3)_*}{1 - v}\right) \cdot \left(-\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\color{blue}{\frac{\left(-4.5\right) \cdot \left(-4.5\right) - 3 \cdot 3}{\left(-4.5\right) - 3}} + \frac{\frac{2}{r}}{r}\right))_* + 0\]
  11. Applied frac-add0.5

    \[\leadsto (\left(0.125 \cdot \frac{(-2 \cdot v + 3)_*}{1 - v}\right) \cdot \left(-\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \color{blue}{\left(\frac{\left(\left(-4.5\right) \cdot \left(-4.5\right) - 3 \cdot 3\right) \cdot r + \left(\left(-4.5\right) - 3\right) \cdot \frac{2}{r}}{\left(\left(-4.5\right) - 3\right) \cdot r}\right)})_* + 0\]
  12. Simplified0.5

    \[\leadsto (\left(0.125 \cdot \frac{(-2 \cdot v + 3)_*}{1 - v}\right) \cdot \left(-\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\frac{\color{blue}{(\left(3 - 4.5\right) \cdot r + \left(\frac{2}{r}\right))_* \cdot \left(-3 - 4.5\right)}}{\left(\left(-4.5\right) - 3\right) \cdot r}\right))_* + 0\]
  13. Simplified0.5

    \[\leadsto (\left(0.125 \cdot \frac{(-2 \cdot v + 3)_*}{1 - v}\right) \cdot \left(-\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\frac{(\left(3 - 4.5\right) \cdot r + \left(\frac{2}{r}\right))_* \cdot \left(-3 - 4.5\right)}{\color{blue}{\left(-3 - 4.5\right) \cdot r}}\right))_* + 0\]
  14. Using strategy rm
  15. Applied flip--0.5

    \[\leadsto (\left(0.125 \cdot \frac{(-2 \cdot v + 3)_*}{1 - v}\right) \cdot \left(-\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\frac{(\left(3 - 4.5\right) \cdot r + \left(\frac{2}{r}\right))_* \cdot \color{blue}{\frac{-3 \cdot -3 - 4.5 \cdot 4.5}{-3 + 4.5}}}{\left(-3 - 4.5\right) \cdot r}\right))_* + 0\]
  16. Applied associate-*r/0.6

    \[\leadsto (\left(0.125 \cdot \frac{(-2 \cdot v + 3)_*}{1 - v}\right) \cdot \left(-\left(w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\frac{\color{blue}{\frac{(\left(3 - 4.5\right) \cdot r + \left(\frac{2}{r}\right))_* \cdot \left(-3 \cdot -3 - 4.5 \cdot 4.5\right)}{-3 + 4.5}}}{\left(-3 - 4.5\right) \cdot r}\right))_* + 0\]
  17. Final simplification0.6

    \[\leadsto (\left(\frac{(-2 \cdot v + 3)_*}{1 - v} \cdot 0.125\right) \cdot \left(\left(-w \cdot r\right) \cdot \left(w \cdot r\right)\right) + \left(\frac{\frac{\left(9 - 4.5 \cdot 4.5\right) \cdot (\left(3 - 4.5\right) \cdot r + \left(\frac{2}{r}\right))_*}{4.5 + -3}}{r \cdot \left(-3 - 4.5\right)}\right))_*\]

Runtime

Time bar (total: 1.3m)Debug logProfile

BaselineHerbieOracleSpan%
Regimes0.60.60.10.50%
herbie shell --seed 2018263 +o rules:numerics
(FPCore (v w r)
  :name "Rosa's TurbineBenchmark"
  (- (- (+ 3 (/ 2 (* r r))) (/ (* (* 0.125 (- 3 (* 2 v))) (* (* (* w w) r) r)) (- 1 v))) 4.5))