Math FPCore C Julia Wolfram TeX \[\left(\left(x \cdot y + \frac{z \cdot t}{16}\right) - \frac{a \cdot b}{4}\right) + c
\]
↓
\[\mathsf{fma}\left(x, y, \mathsf{fma}\left(t, \frac{z}{16}, c - a \cdot \frac{b}{4}\right)\right)
\]
(FPCore (x y z t a b c)
:precision binary64
(+ (- (+ (* x y) (/ (* z t) 16.0)) (/ (* a b) 4.0)) c)) ↓
(FPCore (x y z t a b c)
:precision binary64
(fma x y (fma t (/ z 16.0) (- c (* a (/ b 4.0)))))) double code(double x, double y, double z, double t, double a, double b, double c) {
return (((x * y) + ((z * t) / 16.0)) - ((a * b) / 4.0)) + c;
}
↓
double code(double x, double y, double z, double t, double a, double b, double c) {
return fma(x, y, fma(t, (z / 16.0), (c - (a * (b / 4.0)))));
}
function code(x, y, z, t, a, b, c)
return Float64(Float64(Float64(Float64(x * y) + Float64(Float64(z * t) / 16.0)) - Float64(Float64(a * b) / 4.0)) + c)
end
↓
function code(x, y, z, t, a, b, c)
return fma(x, y, fma(t, Float64(z / 16.0), Float64(c - Float64(a * Float64(b / 4.0)))))
end
code[x_, y_, z_, t_, a_, b_, c_] := N[(N[(N[(N[(x * y), $MachinePrecision] + N[(N[(z * t), $MachinePrecision] / 16.0), $MachinePrecision]), $MachinePrecision] - N[(N[(a * b), $MachinePrecision] / 4.0), $MachinePrecision]), $MachinePrecision] + c), $MachinePrecision]
↓
code[x_, y_, z_, t_, a_, b_, c_] := N[(x * y + N[(t * N[(z / 16.0), $MachinePrecision] + N[(c - N[(a * N[(b / 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\left(\left(x \cdot y + \frac{z \cdot t}{16}\right) - \frac{a \cdot b}{4}\right) + c
↓
\mathsf{fma}\left(x, y, \mathsf{fma}\left(t, \frac{z}{16}, c - a \cdot \frac{b}{4}\right)\right)
Alternatives Alternative 1 Accuracy 65.1% Cost 2528
\[\begin{array}{l}
t_1 := c + t \cdot \left(z \cdot 0.0625\right)\\
t_2 := x \cdot y + 0.0625 \cdot \left(t \cdot z\right)\\
t_3 := c + a \cdot \left(b \cdot -0.25\right)\\
\mathbf{if}\;a \cdot b \leq -4 \cdot 10^{+148}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;a \cdot b \leq -1 \cdot 10^{+61}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;a \cdot b \leq -5 \cdot 10^{-40}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;a \cdot b \leq -2 \cdot 10^{-72}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \cdot b \leq -1 \cdot 10^{-203}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;a \cdot b \leq 2 \cdot 10^{-139}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \cdot b \leq 5 \cdot 10^{-61}:\\
\;\;\;\;c + x \cdot y\\
\mathbf{elif}\;a \cdot b \leq 5 \cdot 10^{-27}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_3\\
\end{array}
\]
Alternative 2 Accuracy 49.1% Cost 1904
\[\begin{array}{l}
t_1 := a \cdot \left(b \cdot -0.25\right)\\
t_2 := c + x \cdot y\\
t_3 := 0.0625 \cdot \left(t \cdot z\right)\\
\mathbf{if}\;x \leq -5.5 \cdot 10^{+75}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -8.8 \cdot 10^{+46}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -51000:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -2.7 \cdot 10^{-54}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;x \leq -3.5 \cdot 10^{-115}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -1.05 \cdot 10^{-160}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;x \leq -1.5 \cdot 10^{-164}:\\
\;\;\;\;c\\
\mathbf{elif}\;x \leq -2.8 \cdot 10^{-179}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -9.5 \cdot 10^{-247}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;x \leq -8.5 \cdot 10^{-298}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq 5.6 \cdot 10^{-304}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 6.2 \cdot 10^{-248}:\\
\;\;\;\;t_3\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 3 Accuracy 66.4% Cost 1768
\[\begin{array}{l}
t_1 := x \cdot y - \left(a \cdot b\right) \cdot 0.25\\
t_2 := x \cdot y + 0.0625 \cdot \left(t \cdot z\right)\\
t_3 := c + a \cdot \left(b \cdot -0.25\right)\\
\mathbf{if}\;c \leq -2.65 \cdot 10^{+20}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;c \leq -2.4 \cdot 10^{-233}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;c \leq 3.8 \cdot 10^{-236}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;c \leq 1.58 \cdot 10^{-152}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;c \leq 1.2 \cdot 10^{-112}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;c \leq 1.35 \cdot 10^{-45}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;c \leq 1450000000:\\
\;\;\;\;t_3\\
\mathbf{elif}\;c \leq 3.9 \cdot 10^{+44}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;c \leq 3.5 \cdot 10^{+70}:\\
\;\;\;\;c + t \cdot \left(z \cdot 0.0625\right)\\
\mathbf{elif}\;c \leq 8 \cdot 10^{+107}:\\
\;\;\;\;c + x \cdot y\\
\mathbf{else}:\\
\;\;\;\;t_3\\
\end{array}
\]
Alternative 4 Accuracy 52.7% Cost 1376
\[\begin{array}{l}
t_1 := c + a \cdot \left(b \cdot -0.25\right)\\
t_2 := c + x \cdot y\\
t_3 := 0.0625 \cdot \left(t \cdot z\right)\\
\mathbf{if}\;z \leq -5.9 \cdot 10^{+249}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;z \leq -1.3 \cdot 10^{+138}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;z \leq -7.8 \cdot 10^{+115}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;z \leq -3.8 \cdot 10^{+16}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;z \leq 3.2 \cdot 10^{-308}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 1.85 \cdot 10^{-245}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;z \leq 4 \cdot 10^{-102}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 7.6 \cdot 10^{-20}:\\
\;\;\;\;t_2\\
\mathbf{else}:\\
\;\;\;\;t_3\\
\end{array}
\]
Alternative 5 Accuracy 62.0% Cost 1240
\[\begin{array}{l}
t_1 := c + x \cdot y\\
t_2 := c + t \cdot \left(z \cdot 0.0625\right)\\
t_3 := c + a \cdot \left(b \cdot -0.25\right)\\
\mathbf{if}\;z \leq -5 \cdot 10^{+40}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;z \leq -1 \cdot 10^{+17}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 3.3 \cdot 10^{-308}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;z \leq 3.4 \cdot 10^{-245}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 4.2 \cdot 10^{-100}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;z \leq 2.1 \cdot 10^{-21}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 6 Accuracy 87.2% Cost 1225
\[\begin{array}{l}
\mathbf{if}\;a \cdot b \leq -4 \cdot 10^{+148} \lor \neg \left(a \cdot b \leq 10^{+150}\right):\\
\;\;\;\;c + a \cdot \left(b \cdot -0.25\right)\\
\mathbf{else}:\\
\;\;\;\;c + \left(x \cdot y + 0.0625 \cdot \left(t \cdot z\right)\right)\\
\end{array}
\]
Alternative 7 Accuracy 89.7% Cost 1225
\[\begin{array}{l}
\mathbf{if}\;a \cdot b \leq -4 \cdot 10^{+148} \lor \neg \left(a \cdot b \leq 5 \cdot 10^{-27}\right):\\
\;\;\;\;\left(c + x \cdot y\right) + \left(a \cdot b\right) \cdot -0.25\\
\mathbf{else}:\\
\;\;\;\;c + \left(x \cdot y + 0.0625 \cdot \left(t \cdot z\right)\right)\\
\end{array}
\]
Alternative 8 Accuracy 99.8% Cost 1152
\[c + \left(\left(\frac{t \cdot z}{16} + x \cdot y\right) - \frac{a}{\frac{-4}{-b}}\right)
\]
Alternative 9 Accuracy 43.5% Cost 1112
\[\begin{array}{l}
t_1 := 0.0625 \cdot \left(t \cdot z\right)\\
\mathbf{if}\;c \leq -7.8 \cdot 10^{+92}:\\
\;\;\;\;c\\
\mathbf{elif}\;c \leq -1.52 \cdot 10^{-246}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;c \leq 4.1 \cdot 10^{-234}:\\
\;\;\;\;x \cdot y\\
\mathbf{elif}\;c \leq 2.55 \cdot 10^{-150}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;c \leq 1.2 \cdot 10^{-117}:\\
\;\;\;\;x \cdot y\\
\mathbf{elif}\;c \leq 1.5 \cdot 10^{-46}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;c\\
\end{array}
\]
Alternative 10 Accuracy 99.8% Cost 1088
\[c + \left(\left(\frac{t \cdot z}{16} + x \cdot y\right) - \frac{a \cdot b}{4}\right)
\]
Alternative 11 Accuracy 44.3% Cost 980
\[\begin{array}{l}
t_1 := 0.0625 \cdot \left(t \cdot z\right)\\
\mathbf{if}\;c \leq -1.85 \cdot 10^{+92}:\\
\;\;\;\;c\\
\mathbf{elif}\;c \leq -1.5 \cdot 10^{-237}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;c \leq 7 \cdot 10^{-234}:\\
\;\;\;\;x \cdot y\\
\mathbf{elif}\;c \leq 1.85 \cdot 10^{-155}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;c \leq 2.6 \cdot 10^{+44}:\\
\;\;\;\;a \cdot \left(b \cdot -0.25\right)\\
\mathbf{else}:\\
\;\;\;\;c\\
\end{array}
\]
Alternative 12 Accuracy 44.8% Cost 456
\[\begin{array}{l}
\mathbf{if}\;c \leq -3.15 \cdot 10^{+29}:\\
\;\;\;\;c\\
\mathbf{elif}\;c \leq 2.1 \cdot 10^{+30}:\\
\;\;\;\;x \cdot y\\
\mathbf{else}:\\
\;\;\;\;c\\
\end{array}
\]
Alternative 13 Accuracy 31.7% Cost 64
\[c
\]