\[{x}^{4} - {y}^{4}
\]
↓
\[{x}^{4} - {y}^{4}
\]
(FPCore (x y) :precision binary64 (- (pow x 4.0) (pow y 4.0)))
↓
(FPCore (x y) :precision binary64 (- (pow x 4.0) (pow y 4.0)))
double code(double x, double y) {
return pow(x, 4.0) - pow(y, 4.0);
}
↓
double code(double x, double y) {
return pow(x, 4.0) - pow(y, 4.0);
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (x ** 4.0d0) - (y ** 4.0d0)
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (x ** 4.0d0) - (y ** 4.0d0)
end function
public static double code(double x, double y) {
return Math.pow(x, 4.0) - Math.pow(y, 4.0);
}
↓
public static double code(double x, double y) {
return Math.pow(x, 4.0) - Math.pow(y, 4.0);
}
def code(x, y):
return math.pow(x, 4.0) - math.pow(y, 4.0)
↓
def code(x, y):
return math.pow(x, 4.0) - math.pow(y, 4.0)
function code(x, y)
return Float64((x ^ 4.0) - (y ^ 4.0))
end
↓
function code(x, y)
return Float64((x ^ 4.0) - (y ^ 4.0))
end
function tmp = code(x, y)
tmp = (x ^ 4.0) - (y ^ 4.0);
end
↓
function tmp = code(x, y)
tmp = (x ^ 4.0) - (y ^ 4.0);
end
code[x_, y_] := N[(N[Power[x, 4.0], $MachinePrecision] - N[Power[y, 4.0], $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_] := N[(N[Power[x, 4.0], $MachinePrecision] - N[Power[y, 4.0], $MachinePrecision]), $MachinePrecision]
{x}^{4} - {y}^{4}
↓
{x}^{4} - {y}^{4}
Alternatives
| Alternative 1 |
|---|
| Accuracy | 99.5% |
|---|
| Cost | 7232 |
|---|
\[\mathsf{fma}\left(x, x, y \cdot y\right) \cdot \left(x \cdot x - y \cdot y\right)
\]
| Alternative 2 |
|---|
| Accuracy | 90.6% |
|---|
| Cost | 1096 |
|---|
\[\begin{array}{l}
t_0 := x \cdot x - y \cdot y\\
\mathbf{if}\;y \leq -1.85 \cdot 10^{-71}:\\
\;\;\;\;\frac{y}{\frac{\frac{-1}{y \cdot y}}{y}}\\
\mathbf{elif}\;y \leq 1.15 \cdot 10^{-56}:\\
\;\;\;\;x \cdot \frac{x}{\frac{1}{t_0}}\\
\mathbf{else}:\\
\;\;\;\;\left(y \cdot y\right) \cdot t_0\\
\end{array}
\]
| Alternative 3 |
|---|
| Accuracy | 90.7% |
|---|
| Cost | 1096 |
|---|
\[\begin{array}{l}
t_0 := x \cdot x - y \cdot y\\
\mathbf{if}\;y \leq -1.85 \cdot 10^{-71}:\\
\;\;\;\;\frac{y}{\frac{\frac{-1}{y \cdot y}}{y}}\\
\mathbf{elif}\;y \leq 6.8 \cdot 10^{-58}:\\
\;\;\;\;x \cdot \frac{x}{\frac{1}{t_0}}\\
\mathbf{else}:\\
\;\;\;\;\frac{y}{\frac{\frac{1}{y}}{t_0}}\\
\end{array}
\]
| Alternative 4 |
|---|
| Accuracy | 90.7% |
|---|
| Cost | 1096 |
|---|
\[\begin{array}{l}
t_0 := \frac{1}{x \cdot x - y \cdot y}\\
\mathbf{if}\;y \leq -1.85 \cdot 10^{-71}:\\
\;\;\;\;\frac{y}{\frac{\frac{-1}{y \cdot y}}{y}}\\
\mathbf{elif}\;y \leq 7 \cdot 10^{-58}:\\
\;\;\;\;x \cdot \frac{x}{t_0}\\
\mathbf{else}:\\
\;\;\;\;\frac{y}{\frac{t_0}{y}}\\
\end{array}
\]
| Alternative 5 |
|---|
| Accuracy | 90.6% |
|---|
| Cost | 968 |
|---|
\[\begin{array}{l}
\mathbf{if}\;y \leq -1.85 \cdot 10^{-71}:\\
\;\;\;\;\frac{y}{\frac{\frac{-1}{y \cdot y}}{y}}\\
\mathbf{elif}\;y \leq 6 \cdot 10^{-57}:\\
\;\;\;\;\left(x \cdot x\right) \cdot \left(x \cdot x\right)\\
\mathbf{else}:\\
\;\;\;\;\left(y \cdot y\right) \cdot \left(x \cdot x - y \cdot y\right)\\
\end{array}
\]
| Alternative 6 |
|---|
| Accuracy | 99.5% |
|---|
| Cost | 960 |
|---|
\[\left(x \cdot x - y \cdot y\right) \cdot \left(y \cdot y + x \cdot x\right)
\]
| Alternative 7 |
|---|
| Accuracy | 90.6% |
|---|
| Cost | 841 |
|---|
\[\begin{array}{l}
\mathbf{if}\;y \leq -1.85 \cdot 10^{-71} \lor \neg \left(y \leq 6.8 \cdot 10^{-58}\right):\\
\;\;\;\;\frac{y}{\frac{\frac{-1}{y \cdot y}}{y}}\\
\mathbf{else}:\\
\;\;\;\;\left(x \cdot x\right) \cdot \left(x \cdot x\right)\\
\end{array}
\]
| Alternative 8 |
|---|
| Accuracy | 90.5% |
|---|
| Cost | 777 |
|---|
\[\begin{array}{l}
\mathbf{if}\;y \leq -1.85 \cdot 10^{-71} \lor \neg \left(y \leq 1.35 \cdot 10^{-57}\right):\\
\;\;\;\;\left(y \cdot y\right) \cdot \left(y \cdot \left(-y\right)\right)\\
\mathbf{else}:\\
\;\;\;\;\left(x \cdot x\right) \cdot \left(x \cdot x\right)\\
\end{array}
\]
| Alternative 9 |
|---|
| Accuracy | 68.7% |
|---|
| Cost | 448 |
|---|
\[\left(x \cdot x\right) \cdot \left(x \cdot x\right)
\]