Radioactive exchange between two surfaces

Percentage Accurate: 86.2% → 99.9%

Time: 6.2s

Alternatives: 6

Speedup: 7.4×

• 60.7% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ {x}^{4} - {y}^{4} \end{array} \]

FPCore

(FPCore (x y) :precision binary64 (- (pow x 4.0) (pow y 4.0)))

C

double code(double x, double y) {
	return pow(x, 4.0) - pow(y, 4.0);
}

Fortran

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

Java

public static double code(double x, double y) {
	return Math.pow(x, 4.0) - Math.pow(y, 4.0);
}

Python

def code(x, y):
	return math.pow(x, 4.0) - math.pow(y, 4.0)

Julia

function code(x, y)
	return Float64((x ^ 4.0) - (y ^ 4.0))
end

MATLAB

function tmp = code(x, y)
	tmp = (x ^ 4.0) - (y ^ 4.0);
end

Wolfram

code[x_, y_] := N[(N[Power[x, 4.0], $MachinePrecision] - N[Power[y, 4.0], $MachinePrecision]), $MachinePrecision]

Initial Program: 86.2% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ {x}^{4} - {y}^{4} \end{array} \]

FPCore

(FPCore (x y) :precision binary64 (- (pow x 4.0) (pow y 4.0)))

C

double code(double x, double y) {
	return pow(x, 4.0) - pow(y, 4.0);
}

Fortran

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

Java

public static double code(double x, double y) {
	return Math.pow(x, 4.0) - Math.pow(y, 4.0);
}

Python

def code(x, y):
	return math.pow(x, 4.0) - math.pow(y, 4.0)

Julia

function code(x, y)
	return Float64((x ^ 4.0) - (y ^ 4.0))
end

MATLAB

function tmp = code(x, y)
	tmp = (x ^ 4.0) - (y ^ 4.0);
end

Wolfram

code[x_, y_] := N[(N[Power[x, 4.0], $MachinePrecision] - N[Power[y, 4.0], $MachinePrecision]), $MachinePrecision]

Alternative 1: 99.9% accurate, 7.4× speedup

Math

\[\begin{array}{l} \\ \left(\left(x - y\right) \cdot \mathsf{fma}\left(y, y, x \cdot x\right)\right) \cdot \left(x + y\right) \end{array} \]

FPCore

(FPCore (x y) :precision binary64 (* (* (- x y) (fma y y (* x x))) (+ x y)))

C

double code(double x, double y) {
	return ((x - y) * fma(y, y, (x * x))) * (x + y);
}

Julia

function code(x, y)
	return Float64(Float64(Float64(x - y) * fma(y, y, Float64(x * x))) * Float64(x + y))
end

Wolfram

code[x_, y_] := N[(N[(N[(x - y), $MachinePrecision] * N[(y * y + N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(x + y), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 85.5%

   \[{x}^{4} - {y}^{4} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \color{blue}{{x}^{4} - {y}^{4}} \]

   2. sub-neg N/A

      \[\leadsto \color{blue}{{x}^{4} + \left(\mathsf{neg}\left({y}^{4}\right)\right)} \]

   3. +-commutative N/A

      \[\leadsto \color{blue}{\left(\mathsf{neg}\left({y}^{4}\right)\right) + {x}^{4}} \]

   4. lift-pow.f64 N/A

      \[\leadsto \left(\mathsf{neg}\left(\color{blue}{{y}^{4}}\right)\right) + {x}^{4} \]

   5. sqr-pow N/A

      \[\leadsto \left(\mathsf{neg}\left(\color{blue}{{y}^{\left(\frac{4}{2}\right)} \cdot {y}^{\left(\frac{4}{2}\right)}}\right)\right) + {x}^{4} \]

   6. distribute-lft-neg-in N/A

      \[\leadsto \color{blue}{\left(\mathsf{neg}\left({y}^{\left(\frac{4}{2}\right)}\right)\right) \cdot {y}^{\left(\frac{4}{2}\right)}} + {x}^{4} \]

   7. metadata-eval N/A

      \[\leadsto \left(\mathsf{neg}\left({y}^{\left(\frac{4}{2}\right)}\right)\right) \cdot {y}^{\color{blue}{2}} + {x}^{4} \]

   8. unpow2 N/A

      \[\leadsto \left(\mathsf{neg}\left({y}^{\left(\frac{4}{2}\right)}\right)\right) \cdot \color{blue}{\left(y \cdot y\right)} + {x}^{4} \]

   9. associate-*r* N/A

      \[\leadsto \color{blue}{\left(\left(\mathsf{neg}\left({y}^{\left(\frac{4}{2}\right)}\right)\right) \cdot y\right) \cdot y} + {x}^{4} \]

   10. lower-fma.f64 N/A

       \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\mathsf{neg}\left({y}^{\left(\frac{4}{2}\right)}\right)\right) \cdot y, y, {x}^{4}\right)} \]

   11. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\mathsf{neg}\left({y}^{\left(\frac{4}{2}\right)}\right)\right) \cdot y}, y, {x}^{4}\right) \]

   12. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(\left(\mathsf{neg}\left({y}^{\color{blue}{2}}\right)\right) \cdot y, y, {x}^{4}\right) \]

   13. unpow2 N/A

       \[\leadsto \mathsf{fma}\left(\left(\mathsf{neg}\left(\color{blue}{y \cdot y}\right)\right) \cdot y, y, {x}^{4}\right) \]

   14. distribute-lft-neg-in N/A

       \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\left(\mathsf{neg}\left(y\right)\right) \cdot y\right)} \cdot y, y, {x}^{4}\right) \]

   15. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(\color{blue}{\left(\left(\mathsf{neg}\left(y\right)\right) \cdot y\right)} \cdot y, y, {x}^{4}\right) \]

   16. lower-neg.f64 87.4

       \[\leadsto \mathsf{fma}\left(\left(\color{blue}{\left(-y\right)} \cdot y\right) \cdot y, y, {x}^{4}\right) \]

4. Applied rewrites 87.4%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\left(-y\right) \cdot y\right) \cdot y, y, {x}^{4}\right)} \]

6. Applied rewrites 78.0%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(y, y, x \cdot x\right), \left(x - y\right) \cdot x, \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x - y\right) \cdot y\right)\right)} \]
7. Step-by-step derivation

   1. lift-fma.f64 N/A

      \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x - y\right) \cdot x\right) + \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x - y\right) \cdot y\right)} \]

   2. lift-*.f64 N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x - y\right) \cdot x\right) + \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x - y\right) \cdot y\right)} \]

   3. lift-*.f64 N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x - y\right) \cdot x\right)} + \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x - y\right) \cdot y\right) \]

   4. associate-*r* N/A

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x - y\right)\right) \cdot x} + \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x - y\right) \cdot y\right) \]

   5. lift-*.f64 N/A

      \[\leadsto \left(\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x - y\right)\right) \cdot x + \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x - y\right) \cdot y\right)} \]

   6. associate-*r* N/A

      \[\leadsto \left(\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x - y\right)\right) \cdot x + \color{blue}{\left(\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x - y\right)\right) \cdot y} \]

   7. distribute-lft-out N/A

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x - y\right)\right) \cdot \left(x + y\right)} \]

   8. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x - y\right)\right) \cdot \left(x + y\right)} \]

   9. *-commutative N/A

      \[\leadsto \color{blue}{\left(\left(x - y\right) \cdot \mathsf{fma}\left(y, y, x \cdot x\right)\right)} \cdot \left(x + y\right) \]

   10. lower-*.f64 N/A

       \[\leadsto \color{blue}{\left(\left(x - y\right) \cdot \mathsf{fma}\left(y, y, x \cdot x\right)\right)} \cdot \left(x + y\right) \]

   11. lower-+.f64 99.8

       \[\leadsto \left(\left(x - y\right) \cdot \mathsf{fma}\left(y, y, x \cdot x\right)\right) \cdot \color{blue}{\left(x + y\right)} \]

8. Applied rewrites 99.8%

   \[\leadsto \color{blue}{\left(\left(x - y\right) \cdot \mathsf{fma}\left(y, y, x \cdot x\right)\right) \cdot \left(x + y\right)} \]
9. Add Preprocessing

Alternative 2: 99.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := {x}^{4} - {y}^{4}\\ \mathbf{if}\;t\_0 \leq -1 \cdot 10^{-323}:\\ \;\;\;\;\left(y \cdot y\right) \cdot \left(\left(-y\right) \cdot y\right)\\ \mathbf{elif}\;t\_0 \leq \infty:\\ \;\;\;\;\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y \cdot y\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y)
 :precision binary64
 (let* ((t_0 (- (pow x 4.0) (pow y 4.0))))
   (if (<= t_0 -1e-323)
     (* (* y y) (* (- y) y))
     (if (<= t_0 INFINITY)
       (* (fma y y (* x x)) (* x x))
       (* (* y y) (* (+ x y) (- x y)))))))

C

double code(double x, double y) {
	double t_0 = pow(x, 4.0) - pow(y, 4.0);
	double tmp;
	if (t_0 <= -1e-323) {
		tmp = (y * y) * (-y * y);
	} else if (t_0 <= ((double) INFINITY)) {
		tmp = fma(y, y, (x * x)) * (x * x);
	} else {
		tmp = (y * y) * ((x + y) * (x - y));
	}
	return tmp;
}

Julia

function code(x, y)
	t_0 = Float64((x ^ 4.0) - (y ^ 4.0))
	tmp = 0.0
	if (t_0 <= -1e-323)
		tmp = Float64(Float64(y * y) * Float64(Float64(-y) * y));
	elseif (t_0 <= Inf)
		tmp = Float64(fma(y, y, Float64(x * x)) * Float64(x * x));
	else
		tmp = Float64(Float64(y * y) * Float64(Float64(x + y) * Float64(x - y)));
	end
	return tmp
end

Wolfram

code[x_, y_] := Block[{t$95$0 = N[(N[Power[x, 4.0], $MachinePrecision] - N[Power[y, 4.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -1e-323], N[(N[(y * y), $MachinePrecision] * N[((-y) * y), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$0, Infinity], N[(N[(y * y + N[(x * x), $MachinePrecision]), $MachinePrecision] * N[(x * x), $MachinePrecision]), $MachinePrecision], N[(N[(y * y), $MachinePrecision] * N[(N[(x + y), $MachinePrecision] * N[(x - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if (-.f64 (pow.f64 x #s(literal 4 binary64)) (pow.f64 y #s(literal 4 binary64))) < -9.88131e-324

   1. Initial program 100.0%

      \[{x}^{4} - {y}^{4} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift--.f64 N/A

         \[\leadsto \color{blue}{{x}^{4} - {y}^{4}} \]

      2. lift-pow.f64 N/A

         \[\leadsto \color{blue}{{x}^{4}} - {y}^{4} \]

      3. sqr-pow N/A

         \[\leadsto \color{blue}{{x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)}} - {y}^{4} \]

      4. lift-pow.f64 N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{4}} \]

      5. sqr-pow N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{\left(\frac{4}{2}\right)} \cdot {y}^{\left(\frac{4}{2}\right)}} \]

      6. difference-of-squares N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      7. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      8. +-commutative N/A

         \[\leadsto \color{blue}{\left({y}^{\left(\frac{4}{2}\right)} + {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      9. metadata-eval N/A

         \[\leadsto \left({y}^{\color{blue}{2}} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      10. unpow2 N/A

          \[\leadsto \left(\color{blue}{y \cdot y} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      11. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      12. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, {x}^{\color{blue}{2}}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      13. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      14. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{\color{blue}{2}} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      16. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{x \cdot x} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      17. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - {y}^{\color{blue}{2}}\right) \]

      18. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - \color{blue}{y \cdot y}\right) \]

      19. difference-of-squares N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      20. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      21. lower-+.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{\left(x + y\right)} \cdot \left(x - y\right)\right) \]

      22. lower--.f64 99.7

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \color{blue}{\left(x - y\right)}\right) \]

   4. Applied rewrites 99.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   5. Taylor expanded in x around inf

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)\right)} \]
   6. Step-by-step derivation

      1. distribute-lft-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)} \]

      2. distribute-lft1-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{\left(\left(-1 + 1\right) \cdot \frac{y}{x}\right)}\right) \]

      3. metadata-eval N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(\color{blue}{0} \cdot \frac{y}{x}\right)\right) \]

      4. mul0-lft N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{0}\right) \]

      5. distribute-lft-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + 0\right)\right)} \]

      6. metadata-eval N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot \color{blue}{1}\right) \]

      7. *-rgt-identity N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{{x}^{2}} \]

      8. unpow2 N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

      9. lower-*.f64 2.0

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   7. Applied rewrites 2.0%

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   8. Taylor expanded in x around 0

      \[\leadsto \color{blue}{{y}^{2}} \cdot \left(x \cdot x\right) \]
   9. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

      2. lower-*.f64 2.0

         \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

   10. Applied rewrites 2.0%

       \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

   11. Taylor expanded in x around 0

       \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(-1 \cdot {y}^{2} + x \cdot \left(y + -1 \cdot y\right)\right)} \]
   12. Step-by-step derivation

       1. distribute-rgt1-in N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + x \cdot \color{blue}{\left(\left(-1 + 1\right) \cdot y\right)}\right) \]

       2. metadata-eval N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + x \cdot \left(\color{blue}{0} \cdot y\right)\right) \]

       3. mul0-lft N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + x \cdot \color{blue}{0}\right) \]

       4. *-commutative N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + \color{blue}{0 \cdot x}\right) \]

       5. mul0-lft N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + \color{blue}{0}\right) \]

       6. +-rgt-identity N/A

          \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(-1 \cdot {y}^{2}\right)} \]

       7. unpow2 N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot \color{blue}{\left(y \cdot y\right)}\right) \]

       8. associate-*r* N/A

          \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(\left(-1 \cdot y\right) \cdot y\right)} \]

       9. lower-*.f64 N/A

          \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(\left(-1 \cdot y\right) \cdot y\right)} \]

       10. mul-1-neg N/A

           \[\leadsto \left(y \cdot y\right) \cdot \left(\color{blue}{\left(\mathsf{neg}\left(y\right)\right)} \cdot y\right) \]

       11. lower-neg.f64 99.7

           \[\leadsto \left(y \cdot y\right) \cdot \left(\color{blue}{\left(-y\right)} \cdot y\right) \]

   13. Applied rewrites 99.7%

       \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(\left(-y\right) \cdot y\right)} \]

   if -9.88131e-324 < (-.f64 (pow.f64 x #s(literal 4 binary64)) (pow.f64 y #s(literal 4 binary64))) < +inf.0

   1. Initial program 100.0%

      \[{x}^{4} - {y}^{4} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift--.f64 N/A

         \[\leadsto \color{blue}{{x}^{4} - {y}^{4}} \]

      2. lift-pow.f64 N/A

         \[\leadsto \color{blue}{{x}^{4}} - {y}^{4} \]

      3. sqr-pow N/A

         \[\leadsto \color{blue}{{x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)}} - {y}^{4} \]

      4. lift-pow.f64 N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{4}} \]

      5. sqr-pow N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{\left(\frac{4}{2}\right)} \cdot {y}^{\left(\frac{4}{2}\right)}} \]

      6. difference-of-squares N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      7. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      8. +-commutative N/A

         \[\leadsto \color{blue}{\left({y}^{\left(\frac{4}{2}\right)} + {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      9. metadata-eval N/A

         \[\leadsto \left({y}^{\color{blue}{2}} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      10. unpow2 N/A

          \[\leadsto \left(\color{blue}{y \cdot y} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      11. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      12. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, {x}^{\color{blue}{2}}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      13. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      14. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{\color{blue}{2}} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      16. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{x \cdot x} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      17. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - {y}^{\color{blue}{2}}\right) \]

      18. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - \color{blue}{y \cdot y}\right) \]

      19. difference-of-squares N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      20. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      21. lower-+.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{\left(x + y\right)} \cdot \left(x - y\right)\right) \]

      22. lower--.f64 99.9

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \color{blue}{\left(x - y\right)}\right) \]

   4. Applied rewrites 99.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   5. Taylor expanded in x around inf

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)\right)} \]
   6. Step-by-step derivation

      1. distribute-lft-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)} \]

      2. distribute-lft1-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{\left(\left(-1 + 1\right) \cdot \frac{y}{x}\right)}\right) \]

      3. metadata-eval N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(\color{blue}{0} \cdot \frac{y}{x}\right)\right) \]

      4. mul0-lft N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{0}\right) \]

      5. distribute-lft-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + 0\right)\right)} \]

      6. metadata-eval N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot \color{blue}{1}\right) \]

      7. *-rgt-identity N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{{x}^{2}} \]

      8. unpow2 N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

      9. lower-*.f64 99.7

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   7. Applied rewrites 99.7%

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   if +inf.0 < (-.f64 (pow.f64 x #s(literal 4 binary64)) (pow.f64 y #s(literal 4 binary64)))

   1. Initial program 0.0%

      \[{x}^{4} - {y}^{4} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift--.f64 N/A

         \[\leadsto \color{blue}{{x}^{4} - {y}^{4}} \]

      2. lift-pow.f64 N/A

         \[\leadsto \color{blue}{{x}^{4}} - {y}^{4} \]

      3. sqr-pow N/A

         \[\leadsto \color{blue}{{x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)}} - {y}^{4} \]

      4. lift-pow.f64 N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{4}} \]

      5. sqr-pow N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{\left(\frac{4}{2}\right)} \cdot {y}^{\left(\frac{4}{2}\right)}} \]

      6. difference-of-squares N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      7. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      8. +-commutative N/A

         \[\leadsto \color{blue}{\left({y}^{\left(\frac{4}{2}\right)} + {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      9. metadata-eval N/A

         \[\leadsto \left({y}^{\color{blue}{2}} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      10. unpow2 N/A

          \[\leadsto \left(\color{blue}{y \cdot y} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      11. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      12. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, {x}^{\color{blue}{2}}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      13. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      14. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{\color{blue}{2}} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      16. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{x \cdot x} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      17. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - {y}^{\color{blue}{2}}\right) \]

      18. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - \color{blue}{y \cdot y}\right) \]

      19. difference-of-squares N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      20. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      21. lower-+.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{\left(x + y\right)} \cdot \left(x - y\right)\right) \]

      22. lower--.f64 100.0

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \color{blue}{\left(x - y\right)}\right) \]

   4. Applied rewrites 100.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   5. Taylor expanded in x around 0

      \[\leadsto \color{blue}{{y}^{2}} \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \]
   6. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \]

      2. lower-*.f64 100.0

         \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \]

   7. Applied rewrites 100.0%

      \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 3: 69.9% accurate, 6.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -1.75 \cdot 10^{+131} \lor \neg \left(x \leq 2.4 \cdot 10^{+128}\right):\\ \;\;\;\;\left(y \cdot y\right) \cdot \left(x \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y \cdot y\right) \cdot \left(\left(-y\right) \cdot y\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y)
 :precision binary64
 (if (or (<= x -1.75e+131) (not (<= x 2.4e+128)))
   (* (* y y) (* x x))
   (* (* y y) (* (- y) y))))

C

double code(double x, double y) {
	double tmp;
	if ((x <= -1.75e+131) || !(x <= 2.4e+128)) {
		tmp = (y * y) * (x * x);
	} else {
		tmp = (y * y) * (-y * y);
	}
	return tmp;
}

Fortran

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8) :: tmp
    if ((x <= (-1.75d+131)) .or. (.not. (x <= 2.4d+128))) then
        tmp = (y * y) * (x * x)
    else
        tmp = (y * y) * (-y * y)
    end if
    code = tmp
end function

Java

public static double code(double x, double y) {
	double tmp;
	if ((x <= -1.75e+131) || !(x <= 2.4e+128)) {
		tmp = (y * y) * (x * x);
	} else {
		tmp = (y * y) * (-y * y);
	}
	return tmp;
}

Python

def code(x, y):
	tmp = 0
	if (x <= -1.75e+131) or not (x <= 2.4e+128):
		tmp = (y * y) * (x * x)
	else:
		tmp = (y * y) * (-y * y)
	return tmp

Julia

function code(x, y)
	tmp = 0.0
	if ((x <= -1.75e+131) || !(x <= 2.4e+128))
		tmp = Float64(Float64(y * y) * Float64(x * x));
	else
		tmp = Float64(Float64(y * y) * Float64(Float64(-y) * y));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y)
	tmp = 0.0;
	if ((x <= -1.75e+131) || ~((x <= 2.4e+128)))
		tmp = (y * y) * (x * x);
	else
		tmp = (y * y) * (-y * y);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_] := If[Or[LessEqual[x, -1.75e+131], N[Not[LessEqual[x, 2.4e+128]], $MachinePrecision]], N[(N[(y * y), $MachinePrecision] * N[(x * x), $MachinePrecision]), $MachinePrecision], N[(N[(y * y), $MachinePrecision] * N[((-y) * y), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if x < -1.7499999999999999e131 or 2.4000000000000002e128 < x

   1. Initial program 64.5%

      \[{x}^{4} - {y}^{4} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift--.f64 N/A

         \[\leadsto \color{blue}{{x}^{4} - {y}^{4}} \]

      2. lift-pow.f64 N/A

         \[\leadsto \color{blue}{{x}^{4}} - {y}^{4} \]

      3. sqr-pow N/A

         \[\leadsto \color{blue}{{x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)}} - {y}^{4} \]

      4. lift-pow.f64 N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{4}} \]

      5. sqr-pow N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{\left(\frac{4}{2}\right)} \cdot {y}^{\left(\frac{4}{2}\right)}} \]

      6. difference-of-squares N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      7. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      8. +-commutative N/A

         \[\leadsto \color{blue}{\left({y}^{\left(\frac{4}{2}\right)} + {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      9. metadata-eval N/A

         \[\leadsto \left({y}^{\color{blue}{2}} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      10. unpow2 N/A

          \[\leadsto \left(\color{blue}{y \cdot y} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      11. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      12. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, {x}^{\color{blue}{2}}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      13. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      14. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{\color{blue}{2}} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      16. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{x \cdot x} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      17. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - {y}^{\color{blue}{2}}\right) \]

      18. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - \color{blue}{y \cdot y}\right) \]

      19. difference-of-squares N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      20. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      21. lower-+.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{\left(x + y\right)} \cdot \left(x - y\right)\right) \]

      22. lower--.f64 100.0

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \color{blue}{\left(x - y\right)}\right) \]

   4. Applied rewrites 100.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   5. Taylor expanded in x around inf

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)\right)} \]
   6. Step-by-step derivation

      1. distribute-lft-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)} \]

      2. distribute-lft1-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{\left(\left(-1 + 1\right) \cdot \frac{y}{x}\right)}\right) \]

      3. metadata-eval N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(\color{blue}{0} \cdot \frac{y}{x}\right)\right) \]

      4. mul0-lft N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{0}\right) \]

      5. distribute-lft-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + 0\right)\right)} \]

      6. metadata-eval N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot \color{blue}{1}\right) \]

      7. *-rgt-identity N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{{x}^{2}} \]

      8. unpow2 N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

      9. lower-*.f64 92.1

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   7. Applied rewrites 92.1%

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   8. Taylor expanded in x around 0

      \[\leadsto \color{blue}{{y}^{2}} \cdot \left(x \cdot x\right) \]
   9. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

      2. lower-*.f64 68.7

         \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

   10. Applied rewrites 68.7%

       \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

   if -1.7499999999999999e131 < x < 2.4000000000000002e128

   1. Initial program 94.4%

      \[{x}^{4} - {y}^{4} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift--.f64 N/A

         \[\leadsto \color{blue}{{x}^{4} - {y}^{4}} \]

      2. lift-pow.f64 N/A

         \[\leadsto \color{blue}{{x}^{4}} - {y}^{4} \]

      3. sqr-pow N/A

         \[\leadsto \color{blue}{{x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)}} - {y}^{4} \]

      4. lift-pow.f64 N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{4}} \]

      5. sqr-pow N/A

         \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{\left(\frac{4}{2}\right)} \cdot {y}^{\left(\frac{4}{2}\right)}} \]

      6. difference-of-squares N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      7. lower-*.f64 N/A

         \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

      8. +-commutative N/A

         \[\leadsto \color{blue}{\left({y}^{\left(\frac{4}{2}\right)} + {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      9. metadata-eval N/A

         \[\leadsto \left({y}^{\color{blue}{2}} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      10. unpow2 N/A

          \[\leadsto \left(\color{blue}{y \cdot y} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      11. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      12. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, {x}^{\color{blue}{2}}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      13. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      14. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{\color{blue}{2}} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      16. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{x \cdot x} - {y}^{\left(\frac{4}{2}\right)}\right) \]

      17. metadata-eval N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - {y}^{\color{blue}{2}}\right) \]

      18. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - \color{blue}{y \cdot y}\right) \]

      19. difference-of-squares N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      20. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

      21. lower-+.f64 N/A

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{\left(x + y\right)} \cdot \left(x - y\right)\right) \]

      22. lower--.f64 99.8

          \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \color{blue}{\left(x - y\right)}\right) \]

   4. Applied rewrites 99.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   5. Taylor expanded in x around inf

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)\right)} \]
   6. Step-by-step derivation

      1. distribute-lft-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)} \]

      2. distribute-lft1-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{\left(\left(-1 + 1\right) \cdot \frac{y}{x}\right)}\right) \]

      3. metadata-eval N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(\color{blue}{0} \cdot \frac{y}{x}\right)\right) \]

      4. mul0-lft N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{0}\right) \]

      5. distribute-lft-in N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + 0\right)\right)} \]

      6. metadata-eval N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot \color{blue}{1}\right) \]

      7. *-rgt-identity N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{{x}^{2}} \]

      8. unpow2 N/A

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

      9. lower-*.f64 44.7

         \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   7. Applied rewrites 44.7%

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   8. Taylor expanded in x around 0

      \[\leadsto \color{blue}{{y}^{2}} \cdot \left(x \cdot x\right) \]
   9. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

      2. lower-*.f64 23.0

         \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

   10. Applied rewrites 23.0%

       \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

   11. Taylor expanded in x around 0

       \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(-1 \cdot {y}^{2} + x \cdot \left(y + -1 \cdot y\right)\right)} \]
   12. Step-by-step derivation

       1. distribute-rgt1-in N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + x \cdot \color{blue}{\left(\left(-1 + 1\right) \cdot y\right)}\right) \]

       2. metadata-eval N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + x \cdot \left(\color{blue}{0} \cdot y\right)\right) \]

       3. mul0-lft N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + x \cdot \color{blue}{0}\right) \]

       4. *-commutative N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + \color{blue}{0 \cdot x}\right) \]

       5. mul0-lft N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot {y}^{2} + \color{blue}{0}\right) \]

       6. +-rgt-identity N/A

          \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(-1 \cdot {y}^{2}\right)} \]

       7. unpow2 N/A

          \[\leadsto \left(y \cdot y\right) \cdot \left(-1 \cdot \color{blue}{\left(y \cdot y\right)}\right) \]

       8. associate-*r* N/A

          \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(\left(-1 \cdot y\right) \cdot y\right)} \]

       9. lower-*.f64 N/A

          \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(\left(-1 \cdot y\right) \cdot y\right)} \]

       10. mul-1-neg N/A

           \[\leadsto \left(y \cdot y\right) \cdot \left(\color{blue}{\left(\mathsf{neg}\left(y\right)\right)} \cdot y\right) \]

       11. lower-neg.f64 77.0

           \[\leadsto \left(y \cdot y\right) \cdot \left(\color{blue}{\left(-y\right)} \cdot y\right) \]

   13. Applied rewrites 77.0%

       \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(\left(-y\right) \cdot y\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 74.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.75 \cdot 10^{+131} \lor \neg \left(x \leq 2.4 \cdot 10^{+128}\right):\\ \;\;\;\;\left(y \cdot y\right) \cdot \left(x \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y \cdot y\right) \cdot \left(\left(-y\right) \cdot y\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 75.1% accurate, 9.4× speedup

Math

\[\begin{array}{l} \\ \left(y \cdot y\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \end{array} \]

FPCore

(FPCore (x y) :precision binary64 (* (* y y) (* (+ x y) (- x y))))

C

double code(double x, double y) {
	return (y * y) * ((x + y) * (x - y));
}

Fortran

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (y * y) * ((x + y) * (x - y))
end function

Java

public static double code(double x, double y) {
	return (y * y) * ((x + y) * (x - y));
}

Python

def code(x, y):
	return (y * y) * ((x + y) * (x - y))

Julia

function code(x, y)
	return Float64(Float64(y * y) * Float64(Float64(x + y) * Float64(x - y)))
end

MATLAB

function tmp = code(x, y)
	tmp = (y * y) * ((x + y) * (x - y));
end

Wolfram

code[x_, y_] := N[(N[(y * y), $MachinePrecision] * N[(N[(x + y), $MachinePrecision] * N[(x - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 85.5%

   \[{x}^{4} - {y}^{4} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \color{blue}{{x}^{4} - {y}^{4}} \]

   2. lift-pow.f64 N/A

      \[\leadsto \color{blue}{{x}^{4}} - {y}^{4} \]

   3. sqr-pow N/A

      \[\leadsto \color{blue}{{x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)}} - {y}^{4} \]

   4. lift-pow.f64 N/A

      \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{4}} \]

   5. sqr-pow N/A

      \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{\left(\frac{4}{2}\right)} \cdot {y}^{\left(\frac{4}{2}\right)}} \]

   6. difference-of-squares N/A

      \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

   7. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

   8. +-commutative N/A

      \[\leadsto \color{blue}{\left({y}^{\left(\frac{4}{2}\right)} + {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   9. metadata-eval N/A

      \[\leadsto \left({y}^{\color{blue}{2}} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   10. unpow2 N/A

       \[\leadsto \left(\color{blue}{y \cdot y} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   11. lower-fma.f64 N/A

       \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   12. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(y, y, {x}^{\color{blue}{2}}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   13. unpow2 N/A

       \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   14. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   15. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{\color{blue}{2}} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   16. unpow2 N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{x \cdot x} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   17. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - {y}^{\color{blue}{2}}\right) \]

   18. unpow2 N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - \color{blue}{y \cdot y}\right) \]

   19. difference-of-squares N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   20. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   21. lower-+.f64 N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{\left(x + y\right)} \cdot \left(x - y\right)\right) \]

   22. lower--.f64 99.8

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \color{blue}{\left(x - y\right)}\right) \]

4. Applied rewrites 99.8%

   \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

5. Taylor expanded in x around 0

   \[\leadsto \color{blue}{{y}^{2}} \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \]
6. Step-by-step derivation

   1. unpow2 N/A

      \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \]

   2. lower-*.f64 77.5

      \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \]

7. Applied rewrites 77.5%

   \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right) \]
8. Add Preprocessing

Alternative 5: 31.6% accurate, 12.9× speedup

Math

\[\begin{array}{l} \\ \left(y \cdot y\right) \cdot \left(x \cdot x\right) \end{array} \]

FPCore

(FPCore (x y) :precision binary64 (* (* y y) (* x x)))

C

double code(double x, double y) {
	return (y * y) * (x * x);
}

Fortran

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (y * y) * (x * x)
end function

Java

public static double code(double x, double y) {
	return (y * y) * (x * x);
}

Python

def code(x, y):
	return (y * y) * (x * x)

Julia

function code(x, y)
	return Float64(Float64(y * y) * Float64(x * x))
end

MATLAB

function tmp = code(x, y)
	tmp = (y * y) * (x * x);
end

Wolfram

code[x_, y_] := N[(N[(y * y), $MachinePrecision] * N[(x * x), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 85.5%

   \[{x}^{4} - {y}^{4} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. lift--.f64 N/A

      \[\leadsto \color{blue}{{x}^{4} - {y}^{4}} \]

   2. lift-pow.f64 N/A

      \[\leadsto \color{blue}{{x}^{4}} - {y}^{4} \]

   3. sqr-pow N/A

      \[\leadsto \color{blue}{{x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)}} - {y}^{4} \]

   4. lift-pow.f64 N/A

      \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{4}} \]

   5. sqr-pow N/A

      \[\leadsto {x}^{\left(\frac{4}{2}\right)} \cdot {x}^{\left(\frac{4}{2}\right)} - \color{blue}{{y}^{\left(\frac{4}{2}\right)} \cdot {y}^{\left(\frac{4}{2}\right)}} \]

   6. difference-of-squares N/A

      \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

   7. lower-*.f64 N/A

      \[\leadsto \color{blue}{\left({x}^{\left(\frac{4}{2}\right)} + {y}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right)} \]

   8. +-commutative N/A

      \[\leadsto \color{blue}{\left({y}^{\left(\frac{4}{2}\right)} + {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   9. metadata-eval N/A

      \[\leadsto \left({y}^{\color{blue}{2}} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   10. unpow2 N/A

       \[\leadsto \left(\color{blue}{y \cdot y} + {x}^{\left(\frac{4}{2}\right)}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   11. lower-fma.f64 N/A

       \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, {x}^{\left(\frac{4}{2}\right)}\right)} \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   12. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(y, y, {x}^{\color{blue}{2}}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   13. unpow2 N/A

       \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   14. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(y, y, \color{blue}{x \cdot x}\right) \cdot \left({x}^{\left(\frac{4}{2}\right)} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   15. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{\color{blue}{2}} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   16. unpow2 N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{x \cdot x} - {y}^{\left(\frac{4}{2}\right)}\right) \]

   17. metadata-eval N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - {y}^{\color{blue}{2}}\right) \]

   18. unpow2 N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(x \cdot x - \color{blue}{y \cdot y}\right) \]

   19. difference-of-squares N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   20. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

   21. lower-+.f64 N/A

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\color{blue}{\left(x + y\right)} \cdot \left(x - y\right)\right) \]

   22. lower--.f64 99.8

       \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \color{blue}{\left(x - y\right)}\right) \]

4. Applied rewrites 99.8%

   \[\leadsto \color{blue}{\mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left(\left(x + y\right) \cdot \left(x - y\right)\right)} \]

5. Taylor expanded in x around inf

   \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)\right)} \]
6. Step-by-step derivation

   1. distribute-lft-in N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(-1 \cdot \frac{y}{x} + \frac{y}{x}\right)\right)} \]

   2. distribute-lft1-in N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{\left(\left(-1 + 1\right) \cdot \frac{y}{x}\right)}\right) \]

   3. metadata-eval N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \left(\color{blue}{0} \cdot \frac{y}{x}\right)\right) \]

   4. mul0-lft N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot 1 + {x}^{2} \cdot \color{blue}{0}\right) \]

   5. distribute-lft-in N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left({x}^{2} \cdot \left(1 + 0\right)\right)} \]

   6. metadata-eval N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \left({x}^{2} \cdot \color{blue}{1}\right) \]

   7. *-rgt-identity N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{{x}^{2}} \]

   8. unpow2 N/A

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

   9. lower-*.f64 58.8

      \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

7. Applied rewrites 58.8%

   \[\leadsto \mathsf{fma}\left(y, y, x \cdot x\right) \cdot \color{blue}{\left(x \cdot x\right)} \]

8. Taylor expanded in x around 0

   \[\leadsto \color{blue}{{y}^{2}} \cdot \left(x \cdot x\right) \]
9. Step-by-step derivation

   1. unpow2 N/A

      \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

   2. lower-*.f64 36.5

      \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]

10. Applied rewrites 36.5%

    \[\leadsto \color{blue}{\left(y \cdot y\right)} \cdot \left(x \cdot x\right) \]
11. Add Preprocessing

Alternative 6: 21.6% accurate, 12.9× speedup

Math

\[\begin{array}{l} \\ \left(y \cdot y\right) \cdot \left(y \cdot y\right) \end{array} \]

FPCore

(FPCore (x y) :precision binary64 (* (* y y) (* y y)))

C

double code(double x, double y) {
	return (y * y) * (y * y);
}

Fortran

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (y * y) * (y * y)
end function

Java

public static double code(double x, double y) {
	return (y * y) * (y * y);
}

Python

def code(x, y):
	return (y * y) * (y * y)

Julia

function code(x, y)
	return Float64(Float64(y * y) * Float64(y * y))
end

MATLAB

function tmp = code(x, y)
	tmp = (y * y) * (y * y);
end

Wolfram

code[x_, y_] := N[(N[(y * y), $MachinePrecision] * N[(y * y), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 85.5%

   \[{x}^{4} - {y}^{4} \]
2. Add Preprocessing

3. Taylor expanded in x around 0

   \[\leadsto \color{blue}{-1 \cdot {y}^{4}} \]
4. Step-by-step derivation

   1. mul-1-neg N/A

      \[\leadsto \color{blue}{\mathsf{neg}\left({y}^{4}\right)} \]

   2. lower-neg.f64 N/A

      \[\leadsto \color{blue}{-{y}^{4}} \]

   3. lower-pow.f64 56.8

      \[\leadsto -\color{blue}{{y}^{4}} \]

5. Applied rewrites 56.8%

   \[\leadsto \color{blue}{-{y}^{4}} \]

7. Applied rewrites 24.5%

   \[\leadsto \left(y \cdot y\right) \cdot \color{blue}{\left(y \cdot y\right)} \]
8. Add Preprocessing

Reproduce

herbie shell --seed 2024299 
(FPCore (x y)
  :name "Radioactive exchange between two surfaces"
  :precision binary64
  (- (pow x 4.0) (pow y 4.0)))