Bouland and Aaronson, Equation (25)

Percentage Accurate: 73.5% → 99.9%

Time: 8.6s

Alternatives: 11

Speedup: 6.4×

• 60.6% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (-
  (+
   (pow (+ (* a a) (* b b)) 2.0)
   (* 4.0 (+ (* (* a a) (+ 1.0 a)) (* (* b b) (- 1.0 (* 3.0 a))))))
  1.0))

C

double code(double a, double b) {
	return (pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(a, b)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    code = ((((a * a) + (b * b)) ** 2.0d0) + (4.0d0 * (((a * a) * (1.0d0 + a)) + ((b * b) * (1.0d0 - (3.0d0 * a)))))) - 1.0d0
end function

Java

public static double code(double a, double b) {
	return (Math.pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0;
}

Python

def code(a, b):
	return (math.pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0

Julia

function code(a, b)
	return Float64(Float64((Float64(Float64(a * a) + Float64(b * b)) ^ 2.0) + Float64(4.0 * Float64(Float64(Float64(a * a) * Float64(1.0 + a)) + Float64(Float64(b * b) * Float64(1.0 - Float64(3.0 * a)))))) - 1.0)
end

MATLAB

function tmp = code(a, b)
	tmp = ((((a * a) + (b * b)) ^ 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0;
end

Wolfram

code[a_, b_] := N[(N[(N[Power[N[(N[(a * a), $MachinePrecision] + N[(b * b), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(4.0 * N[(N[(N[(a * a), $MachinePrecision] * N[(1.0 + a), $MachinePrecision]), $MachinePrecision] + N[(N[(b * b), $MachinePrecision] * N[(1.0 - N[(3.0 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]

Initial Program: 73.5% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (-
  (+
   (pow (+ (* a a) (* b b)) 2.0)
   (* 4.0 (+ (* (* a a) (+ 1.0 a)) (* (* b b) (- 1.0 (* 3.0 a))))))
  1.0))

C

double code(double a, double b) {
	return (pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(a, b)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    code = ((((a * a) + (b * b)) ** 2.0d0) + (4.0d0 * (((a * a) * (1.0d0 + a)) + ((b * b) * (1.0d0 - (3.0d0 * a)))))) - 1.0d0
end function

Java

public static double code(double a, double b) {
	return (Math.pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0;
}

Python

def code(a, b):
	return (math.pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0

Julia

function code(a, b)
	return Float64(Float64((Float64(Float64(a * a) + Float64(b * b)) ^ 2.0) + Float64(4.0 * Float64(Float64(Float64(a * a) * Float64(1.0 + a)) + Float64(Float64(b * b) * Float64(1.0 - Float64(3.0 * a)))))) - 1.0)
end

MATLAB

function tmp = code(a, b)
	tmp = ((((a * a) + (b * b)) ^ 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0;
end

Wolfram

code[a_, b_] := N[(N[(N[Power[N[(N[(a * a), $MachinePrecision] + N[(b * b), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(4.0 * N[(N[(N[(a * a), $MachinePrecision] * N[(1.0 + a), $MachinePrecision]), $MachinePrecision] + N[(N[(b * b), $MachinePrecision] * N[(1.0 - N[(3.0 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]

Alternative 1: 99.9% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1\\ \mathbf{if}\;t\_0 \leq \infty:\\ \;\;\;\;t\_0\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot a\right) \cdot a - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (let* ((t_0
         (-
          (+
           (pow (+ (* a a) (* b b)) 2.0)
           (* 4.0 (+ (* (* a a) (+ 1.0 a)) (* (* b b) (- 1.0 (* 3.0 a))))))
          1.0)))
   (if (<= t_0 INFINITY)
     t_0
     (- (* (* (fma (+ 4.0 a) a (fma (* b b) 2.0 4.0)) a) a) 1.0))))

C

double code(double a, double b) {
	double t_0 = (pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0;
	double tmp;
	if (t_0 <= ((double) INFINITY)) {
		tmp = t_0;
	} else {
		tmp = ((fma((4.0 + a), a, fma((b * b), 2.0, 4.0)) * a) * a) - 1.0;
	}
	return tmp;
}

Julia

function code(a, b)
	t_0 = Float64(Float64((Float64(Float64(a * a) + Float64(b * b)) ^ 2.0) + Float64(4.0 * Float64(Float64(Float64(a * a) * Float64(1.0 + a)) + Float64(Float64(b * b) * Float64(1.0 - Float64(3.0 * a)))))) - 1.0)
	tmp = 0.0
	if (t_0 <= Inf)
		tmp = t_0;
	else
		tmp = Float64(Float64(Float64(fma(Float64(4.0 + a), a, fma(Float64(b * b), 2.0, 4.0)) * a) * a) - 1.0);
	end
	return tmp
end

Wolfram

code[a_, b_] := Block[{t$95$0 = N[(N[(N[Power[N[(N[(a * a), $MachinePrecision] + N[(b * b), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(4.0 * N[(N[(N[(a * a), $MachinePrecision] * N[(1.0 + a), $MachinePrecision]), $MachinePrecision] + N[(N[(b * b), $MachinePrecision] * N[(1.0 - N[(3.0 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]}, If[LessEqual[t$95$0, Infinity], t$95$0, N[(N[(N[(N[(N[(4.0 + a), $MachinePrecision] * a + N[(N[(b * b), $MachinePrecision] * 2.0 + 4.0), $MachinePrecision]), $MachinePrecision] * a), $MachinePrecision] * a), $MachinePrecision] - 1.0), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (-.f64 (+.f64 (pow.f64 (+.f64 (*.f64 a a) (*.f64 b b)) #s(literal 2 binary64)) (*.f64 #s(literal 4 binary64) (+.f64 (*.f64 (*.f64 a a) (+.f64 #s(literal 1 binary64) a)) (*.f64 (*.f64 b b) (-.f64 #s(literal 1 binary64) (*.f64 #s(literal 3 binary64) a)))))) #s(literal 1 binary64)) < +inf.0

   1. Initial program 99.9%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   if +inf.0 < (-.f64 (+.f64 (pow.f64 (+.f64 (*.f64 a a) (*.f64 b b)) #s(literal 2 binary64)) (*.f64 #s(literal 4 binary64) (+.f64 (*.f64 (*.f64 a a) (+.f64 #s(literal 1 binary64) a)) (*.f64 (*.f64 b b) (-.f64 #s(literal 1 binary64) (*.f64 #s(literal 3 binary64) a)))))) #s(literal 1 binary64))

   1. Initial program 0.0%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4} \cdot \left(1 + \left(2 \cdot \frac{{b}^{2}}{{a}^{2}} + \left(4 \cdot \frac{1}{a} + \frac{4}{{a}^{2}}\right)\right)\right)} - 1 \]

   5. Applied rewrites 100.0%

      \[\leadsto \color{blue}{\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot {a}^{4}} - 1 \]

   6. Taylor expanded in a around 0

      \[\leadsto {a}^{2} \cdot \color{blue}{\left(\left(4 + a \cdot \left(4 + a\right)\right) - -2 \cdot {b}^{2}\right)} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 100.0%

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot a\right) \cdot \color{blue}{a} - 1 \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 2: 84.9% accurate, 3.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 6.4 \cdot 10^{-10}:\\ \;\;\;\;\left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, b, 4\right), \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right) - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 6.4e-10)
   (- (* (* (fma (+ 4.0 a) a 4.0) a) a) 1.0)
   (- (fma (* b b) (fma b b 4.0) (* (* (fma (* b b) 2.0 4.0) a) a)) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if (b <= 6.4e-10) {
		tmp = ((fma((4.0 + a), a, 4.0) * a) * a) - 1.0;
	} else {
		tmp = fma((b * b), fma(b, b, 4.0), ((fma((b * b), 2.0, 4.0) * a) * a)) - 1.0;
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 6.4e-10)
		tmp = Float64(Float64(Float64(fma(Float64(4.0 + a), a, 4.0) * a) * a) - 1.0);
	else
		tmp = Float64(fma(Float64(b * b), fma(b, b, 4.0), Float64(Float64(fma(Float64(b * b), 2.0, 4.0) * a) * a)) - 1.0);
	end
	return tmp
end

Wolfram

code[a_, b_] := If[LessEqual[b, 6.4e-10], N[(N[(N[(N[(N[(4.0 + a), $MachinePrecision] * a + 4.0), $MachinePrecision] * a), $MachinePrecision] * a), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(N[(b * b), $MachinePrecision] * N[(b * b + 4.0), $MachinePrecision] + N[(N[(N[(N[(b * b), $MachinePrecision] * 2.0 + 4.0), $MachinePrecision] * a), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 6.39999999999999961e-10

   1. Initial program 79.1%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4} \cdot \left(1 + \left(2 \cdot \frac{{b}^{2}}{{a}^{2}} + \left(4 \cdot \frac{1}{a} + \frac{4}{{a}^{2}}\right)\right)\right)} - 1 \]

   5. Applied rewrites 64.8%

      \[\leadsto \color{blue}{\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot {a}^{4}} - 1 \]

   6. Taylor expanded in a around 0

      \[\leadsto {a}^{2} \cdot \color{blue}{\left(\left(4 + a \cdot \left(4 + a\right)\right) - -2 \cdot {b}^{2}\right)} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 89.3%

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot a\right) \cdot \color{blue}{a} - 1 \]

   9. Taylor expanded in b around 0

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1 \]
   10. Step-by-step derivation

   11. Applied rewrites 82.0%

       \[\leadsto \left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1 \]

   if 6.39999999999999961e-10 < b

   1. Initial program 69.0%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + \left(a \cdot \left(-12 \cdot {b}^{2} + a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right) + {b}^{4}\right)\right)} - 1 \]
   4. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \color{blue}{\left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2} + a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right) - 1 \]

      2. distribute-lft-in N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \left({b}^{4} + \color{blue}{\left(a \cdot \left(-12 \cdot {b}^{2}\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right)\right) - 1 \]

      3. associate-+r+ N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \color{blue}{\left(\left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2}\right)\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right) - 1 \]

      4. associate-+r+ N/A

         \[\leadsto \color{blue}{\left(\left(4 \cdot {b}^{2} + \left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2}\right)\right)\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)} - 1 \]

   5. Applied rewrites 95.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, b, \mathsf{fma}\left(-12, a, 4\right)\right), \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right)} - 1 \]

   6. Taylor expanded in a around 0

      \[\leadsto \mathsf{fma}\left(b \cdot b, 4 + \color{blue}{{b}^{2}}, \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right) - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 95.9%

      \[\leadsto \mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, \color{blue}{b}, 4\right), \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right) - 1 \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 3: 84.9% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 6.4 \cdot 10^{-10}:\\ \;\;\;\;\left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, b, 4\right), \left(\left(\left(b \cdot b\right) \cdot 2\right) \cdot a\right) \cdot a\right) - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 6.4e-10)
   (- (* (* (fma (+ 4.0 a) a 4.0) a) a) 1.0)
   (- (fma (* b b) (fma b b 4.0) (* (* (* (* b b) 2.0) a) a)) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if (b <= 6.4e-10) {
		tmp = ((fma((4.0 + a), a, 4.0) * a) * a) - 1.0;
	} else {
		tmp = fma((b * b), fma(b, b, 4.0), ((((b * b) * 2.0) * a) * a)) - 1.0;
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 6.4e-10)
		tmp = Float64(Float64(Float64(fma(Float64(4.0 + a), a, 4.0) * a) * a) - 1.0);
	else
		tmp = Float64(fma(Float64(b * b), fma(b, b, 4.0), Float64(Float64(Float64(Float64(b * b) * 2.0) * a) * a)) - 1.0);
	end
	return tmp
end

Wolfram

code[a_, b_] := If[LessEqual[b, 6.4e-10], N[(N[(N[(N[(N[(4.0 + a), $MachinePrecision] * a + 4.0), $MachinePrecision] * a), $MachinePrecision] * a), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(N[(b * b), $MachinePrecision] * N[(b * b + 4.0), $MachinePrecision] + N[(N[(N[(N[(b * b), $MachinePrecision] * 2.0), $MachinePrecision] * a), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 6.39999999999999961e-10

   1. Initial program 79.1%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4} \cdot \left(1 + \left(2 \cdot \frac{{b}^{2}}{{a}^{2}} + \left(4 \cdot \frac{1}{a} + \frac{4}{{a}^{2}}\right)\right)\right)} - 1 \]

   5. Applied rewrites 64.8%

      \[\leadsto \color{blue}{\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot {a}^{4}} - 1 \]

   6. Taylor expanded in a around 0

      \[\leadsto {a}^{2} \cdot \color{blue}{\left(\left(4 + a \cdot \left(4 + a\right)\right) - -2 \cdot {b}^{2}\right)} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 89.3%

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot a\right) \cdot \color{blue}{a} - 1 \]

   9. Taylor expanded in b around 0

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1 \]
   10. Step-by-step derivation

   11. Applied rewrites 82.0%

       \[\leadsto \left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1 \]

   if 6.39999999999999961e-10 < b

   1. Initial program 69.0%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + \left(a \cdot \left(-12 \cdot {b}^{2} + a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right) + {b}^{4}\right)\right)} - 1 \]
   4. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \color{blue}{\left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2} + a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right) - 1 \]

      2. distribute-lft-in N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \left({b}^{4} + \color{blue}{\left(a \cdot \left(-12 \cdot {b}^{2}\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right)\right) - 1 \]

      3. associate-+r+ N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \color{blue}{\left(\left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2}\right)\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right) - 1 \]

      4. associate-+r+ N/A

         \[\leadsto \color{blue}{\left(\left(4 \cdot {b}^{2} + \left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2}\right)\right)\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)} - 1 \]

   5. Applied rewrites 95.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, b, \mathsf{fma}\left(-12, a, 4\right)\right), \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right)} - 1 \]

   6. Taylor expanded in a around 0

      \[\leadsto \mathsf{fma}\left(b \cdot b, 4 + \color{blue}{{b}^{2}}, \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right) - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 95.9%

      \[\leadsto \mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, \color{blue}{b}, 4\right), \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right) - 1 \]

   9. Taylor expanded in b around inf

      \[\leadsto \mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, b, 4\right), \left(2 \cdot \left(a \cdot {b}^{2}\right)\right) \cdot a\right) - 1 \]
   10. Step-by-step derivation

   11. Applied rewrites 95.9%

       \[\leadsto \mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, b, 4\right), \left(\left(\left(b \cdot b\right) \cdot 2\right) \cdot a\right) \cdot a\right) - 1 \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 4: 97.0% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -0.027 \lor \neg \left(a \leq 1.3 \cdot 10^{+48}\right):\\ \;\;\;\;\left(\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot a\right) \cdot a - 1\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(b, b, \mathsf{fma}\left(-12, a, 4\right)\right) \cdot b\right) \cdot b - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (or (<= a -0.027) (not (<= a 1.3e+48)))
   (- (* (* (fma (+ 4.0 a) a (fma (* b b) 2.0 4.0)) a) a) 1.0)
   (- (* (* (fma b b (fma -12.0 a 4.0)) b) b) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if ((a <= -0.027) || !(a <= 1.3e+48)) {
		tmp = ((fma((4.0 + a), a, fma((b * b), 2.0, 4.0)) * a) * a) - 1.0;
	} else {
		tmp = ((fma(b, b, fma(-12.0, a, 4.0)) * b) * b) - 1.0;
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if ((a <= -0.027) || !(a <= 1.3e+48))
		tmp = Float64(Float64(Float64(fma(Float64(4.0 + a), a, fma(Float64(b * b), 2.0, 4.0)) * a) * a) - 1.0);
	else
		tmp = Float64(Float64(Float64(fma(b, b, fma(-12.0, a, 4.0)) * b) * b) - 1.0);
	end
	return tmp
end

Wolfram

code[a_, b_] := If[Or[LessEqual[a, -0.027], N[Not[LessEqual[a, 1.3e+48]], $MachinePrecision]], N[(N[(N[(N[(N[(4.0 + a), $MachinePrecision] * a + N[(N[(b * b), $MachinePrecision] * 2.0 + 4.0), $MachinePrecision]), $MachinePrecision] * a), $MachinePrecision] * a), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(N[(N[(b * b + N[(-12.0 * a + 4.0), $MachinePrecision]), $MachinePrecision] * b), $MachinePrecision] * b), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if a < -0.0269999999999999997 or 1.29999999999999998e48 < a

   1. Initial program 44.6%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4} \cdot \left(1 + \left(2 \cdot \frac{{b}^{2}}{{a}^{2}} + \left(4 \cdot \frac{1}{a} + \frac{4}{{a}^{2}}\right)\right)\right)} - 1 \]

   5. Applied rewrites 99.2%

      \[\leadsto \color{blue}{\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot {a}^{4}} - 1 \]

   6. Taylor expanded in a around 0

      \[\leadsto {a}^{2} \cdot \color{blue}{\left(\left(4 + a \cdot \left(4 + a\right)\right) - -2 \cdot {b}^{2}\right)} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 99.1%

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot a\right) \cdot \color{blue}{a} - 1 \]

   if -0.0269999999999999997 < a < 1.29999999999999998e48

   1. Initial program 98.6%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(-12 \cdot \left(a \cdot {b}^{2}\right) + \left(4 \cdot {b}^{2} + {b}^{4}\right)\right)} - 1 \]
   4. Step-by-step derivation

      1. associate-+r+ N/A

         \[\leadsto \color{blue}{\left(\left(-12 \cdot \left(a \cdot {b}^{2}\right) + 4 \cdot {b}^{2}\right) + {b}^{4}\right)} - 1 \]

      2. +-commutative N/A

         \[\leadsto \color{blue}{\left({b}^{4} + \left(-12 \cdot \left(a \cdot {b}^{2}\right) + 4 \cdot {b}^{2}\right)\right)} - 1 \]

      3. metadata-eval N/A

         \[\leadsto \left({b}^{\color{blue}{\left(2 \cdot 2\right)}} + \left(-12 \cdot \left(a \cdot {b}^{2}\right) + 4 \cdot {b}^{2}\right)\right) - 1 \]

      4. pow-sqr N/A

         \[\leadsto \left(\color{blue}{{b}^{2} \cdot {b}^{2}} + \left(-12 \cdot \left(a \cdot {b}^{2}\right) + 4 \cdot {b}^{2}\right)\right) - 1 \]

      5. associate-*r* N/A

         \[\leadsto \left({b}^{2} \cdot {b}^{2} + \left(\color{blue}{\left(-12 \cdot a\right) \cdot {b}^{2}} + 4 \cdot {b}^{2}\right)\right) - 1 \]

      6. distribute-rgt-out N/A

         \[\leadsto \left({b}^{2} \cdot {b}^{2} + \color{blue}{{b}^{2} \cdot \left(-12 \cdot a + 4\right)}\right) - 1 \]

      7. distribute-lft-out N/A

         \[\leadsto \color{blue}{{b}^{2} \cdot \left({b}^{2} + \left(-12 \cdot a + 4\right)\right)} - 1 \]

      8. lower-*.f64 N/A

         \[\leadsto \color{blue}{{b}^{2} \cdot \left({b}^{2} + \left(-12 \cdot a + 4\right)\right)} - 1 \]

      9. unpow2 N/A

         \[\leadsto \color{blue}{\left(b \cdot b\right)} \cdot \left({b}^{2} + \left(-12 \cdot a + 4\right)\right) - 1 \]

      10. lower-*.f64 N/A

          \[\leadsto \color{blue}{\left(b \cdot b\right)} \cdot \left({b}^{2} + \left(-12 \cdot a + 4\right)\right) - 1 \]

      11. unpow2 N/A

          \[\leadsto \left(b \cdot b\right) \cdot \left(\color{blue}{b \cdot b} + \left(-12 \cdot a + 4\right)\right) - 1 \]

      12. lower-fma.f64 N/A

          \[\leadsto \left(b \cdot b\right) \cdot \color{blue}{\mathsf{fma}\left(b, b, -12 \cdot a + 4\right)} - 1 \]

      13. lower-fma.f64 98.2

          \[\leadsto \left(b \cdot b\right) \cdot \mathsf{fma}\left(b, b, \color{blue}{\mathsf{fma}\left(-12, a, 4\right)}\right) - 1 \]

   5. Applied rewrites 98.2%

      \[\leadsto \color{blue}{\left(b \cdot b\right) \cdot \mathsf{fma}\left(b, b, \mathsf{fma}\left(-12, a, 4\right)\right)} - 1 \]
   6. Step-by-step derivation

   7. Applied rewrites 98.2%

      \[\leadsto \color{blue}{\left(\mathsf{fma}\left(b, b, \mathsf{fma}\left(-12, a, 4\right)\right) \cdot b\right) \cdot b - 1} \]
3. Recombined 2 regimes into one program.

4. Final simplification 98.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -0.027 \lor \neg \left(a \leq 1.3 \cdot 10^{+48}\right):\\ \;\;\;\;\left(\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot a\right) \cdot a - 1\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(b, b, \mathsf{fma}\left(-12, a, 4\right)\right) \cdot b\right) \cdot b - 1\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 83.0% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 1.5:\\ \;\;\;\;\left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(b, b, 4\right) \cdot b\right) \cdot b - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 1.5)
   (- (* (* (fma (+ 4.0 a) a 4.0) a) a) 1.0)
   (- (* (* (fma b b 4.0) b) b) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if (b <= 1.5) {
		tmp = ((fma((4.0 + a), a, 4.0) * a) * a) - 1.0;
	} else {
		tmp = ((fma(b, b, 4.0) * b) * b) - 1.0;
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 1.5)
		tmp = Float64(Float64(Float64(fma(Float64(4.0 + a), a, 4.0) * a) * a) - 1.0);
	else
		tmp = Float64(Float64(Float64(fma(b, b, 4.0) * b) * b) - 1.0);
	end
	return tmp
end

Wolfram

code[a_, b_] := If[LessEqual[b, 1.5], N[(N[(N[(N[(N[(4.0 + a), $MachinePrecision] * a + 4.0), $MachinePrecision] * a), $MachinePrecision] * a), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(N[(N[(b * b + 4.0), $MachinePrecision] * b), $MachinePrecision] * b), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 1.5

   1. Initial program 79.4%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4} \cdot \left(1 + \left(2 \cdot \frac{{b}^{2}}{{a}^{2}} + \left(4 \cdot \frac{1}{a} + \frac{4}{{a}^{2}}\right)\right)\right)} - 1 \]

   5. Applied rewrites 65.1%

      \[\leadsto \color{blue}{\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot {a}^{4}} - 1 \]

   6. Taylor expanded in a around 0

      \[\leadsto {a}^{2} \cdot \color{blue}{\left(\left(4 + a \cdot \left(4 + a\right)\right) - -2 \cdot {b}^{2}\right)} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 89.4%

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot a\right) \cdot \color{blue}{a} - 1 \]

   9. Taylor expanded in b around 0

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1 \]
   10. Step-by-step derivation

   11. Applied rewrites 82.2%

       \[\leadsto \left(\mathsf{fma}\left(4 + a, a, 4\right) \cdot a\right) \cdot a - 1 \]

   if 1.5 < b

   1. Initial program 68.1%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + {b}^{4}\right)} - 1 \]
   4. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \left(4 \cdot \color{blue}{\left(b \cdot b\right)} + {b}^{4}\right) - 1 \]

      2. associate-*r* N/A

         \[\leadsto \left(\color{blue}{\left(4 \cdot b\right) \cdot b} + {b}^{4}\right) - 1 \]

      3. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{\left(2 \cdot 2\right)}}\right) - 1 \]

      4. pow-sqr N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{2} \cdot {b}^{2}}\right) - 1 \]

      5. unpow2 N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{2} \cdot \color{blue}{\left(b \cdot b\right)}\right) - 1 \]

      6. associate-*r* N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left({b}^{2} \cdot b\right) \cdot b}\right) - 1 \]

      7. pow-plus N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      8. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{3}} \cdot b\right) - 1 \]

      9. cube-unmult N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left(b \cdot \left(b \cdot b\right)\right)} \cdot b\right) - 1 \]

      10. unpow2 N/A

          \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \left(b \cdot \color{blue}{{b}^{2}}\right) \cdot b\right) - 1 \]

      11. associate-*r* N/A

          \[\leadsto \left(\color{blue}{4 \cdot \left(b \cdot b\right)} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      12. unpow2 N/A

          \[\leadsto \left(4 \cdot \color{blue}{{b}^{2}} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      13. *-commutative N/A

          \[\leadsto \left(\color{blue}{{b}^{2} \cdot 4} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      14. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \left(b \cdot \color{blue}{\left(b \cdot b\right)}\right) \cdot b\right) - 1 \]

      15. cube-unmult N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{3}} \cdot b\right) - 1 \]

      16. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      17. pow-plus N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{\left({b}^{2} \cdot b\right)} \cdot b\right) - 1 \]

      18. associate-*r* N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{2} \cdot \left(b \cdot b\right)}\right) - 1 \]

      19. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{2} \cdot \color{blue}{{b}^{2}}\right) - 1 \]

      20. pow-sqr N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{\left(2 \cdot 2\right)}}\right) - 1 \]

      21. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{4}}\right) - 1 \]

      22. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left({b}^{2}, 4, {b}^{4}\right)} - 1 \]

      23. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      24. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      25. lower-pow.f64 93.0

          \[\leadsto \mathsf{fma}\left(b \cdot b, 4, \color{blue}{{b}^{4}}\right) - 1 \]

   5. Applied rewrites 93.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, 4, {b}^{4}\right)} - 1 \]
   6. Step-by-step derivation

   7. Applied rewrites 93.0%

      \[\leadsto \left(b \cdot b\right) \cdot \color{blue}{\mathsf{fma}\left(b, b, 4\right)} - 1 \]
   8. Step-by-step derivation

   9. Applied rewrites 93.0%

      \[\leadsto \left(\mathsf{fma}\left(b, b, 4\right) \cdot b\right) \cdot \color{blue}{b} - 1 \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 6: 82.6% accurate, 5.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -3.2 \lor \neg \left(a \leq 7.5 \cdot 10^{+26}\right):\\ \;\;\;\;\left(a \cdot a\right) \cdot \left(a \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot 4 - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (or (<= a -3.2) (not (<= a 7.5e+26)))
   (* (* a a) (* a a))
   (- (* (* b b) 4.0) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if ((a <= -3.2) || !(a <= 7.5e+26)) {
		tmp = (a * a) * (a * a);
	} else {
		tmp = ((b * b) * 4.0) - 1.0;
	}
	return tmp;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(a, b)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8) :: tmp
    if ((a <= (-3.2d0)) .or. (.not. (a <= 7.5d+26))) then
        tmp = (a * a) * (a * a)
    else
        tmp = ((b * b) * 4.0d0) - 1.0d0
    end if
    code = tmp
end function

Java

public static double code(double a, double b) {
	double tmp;
	if ((a <= -3.2) || !(a <= 7.5e+26)) {
		tmp = (a * a) * (a * a);
	} else {
		tmp = ((b * b) * 4.0) - 1.0;
	}
	return tmp;
}

Python

def code(a, b):
	tmp = 0
	if (a <= -3.2) or not (a <= 7.5e+26):
		tmp = (a * a) * (a * a)
	else:
		tmp = ((b * b) * 4.0) - 1.0
	return tmp

Julia

function code(a, b)
	tmp = 0.0
	if ((a <= -3.2) || !(a <= 7.5e+26))
		tmp = Float64(Float64(a * a) * Float64(a * a));
	else
		tmp = Float64(Float64(Float64(b * b) * 4.0) - 1.0);
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b)
	tmp = 0.0;
	if ((a <= -3.2) || ~((a <= 7.5e+26)))
		tmp = (a * a) * (a * a);
	else
		tmp = ((b * b) * 4.0) - 1.0;
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_] := If[Or[LessEqual[a, -3.2], N[Not[LessEqual[a, 7.5e+26]], $MachinePrecision]], N[(N[(a * a), $MachinePrecision] * N[(a * a), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b * b), $MachinePrecision] * 4.0), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if a < -3.2000000000000002 or 7.49999999999999941e26 < a

   1. Initial program 48.1%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + \left(a \cdot \left(-12 \cdot {b}^{2} + a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right) + {b}^{4}\right)\right)} - 1 \]
   4. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \color{blue}{\left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2} + a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right) - 1 \]

      2. distribute-lft-in N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \left({b}^{4} + \color{blue}{\left(a \cdot \left(-12 \cdot {b}^{2}\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right)\right) - 1 \]

      3. associate-+r+ N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \color{blue}{\left(\left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2}\right)\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right) - 1 \]

      4. associate-+r+ N/A

         \[\leadsto \color{blue}{\left(\left(4 \cdot {b}^{2} + \left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2}\right)\right)\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)} - 1 \]

   5. Applied rewrites 71.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, b, \mathsf{fma}\left(-12, a, 4\right)\right), \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right)} - 1 \]

   6. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4}} \]
   7. Step-by-step derivation

      1. lower-pow.f64 88.2

         \[\leadsto \color{blue}{{a}^{4}} \]

   8. Applied rewrites 88.2%

      \[\leadsto \color{blue}{{a}^{4}} \]
   9. Step-by-step derivation

   10. Applied rewrites 88.1%

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

   if -3.2000000000000002 < a < 7.49999999999999941e26

   1. Initial program 98.5%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + {b}^{4}\right)} - 1 \]
   4. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \left(4 \cdot \color{blue}{\left(b \cdot b\right)} + {b}^{4}\right) - 1 \]

      2. associate-*r* N/A

         \[\leadsto \left(\color{blue}{\left(4 \cdot b\right) \cdot b} + {b}^{4}\right) - 1 \]

      3. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{\left(2 \cdot 2\right)}}\right) - 1 \]

      4. pow-sqr N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{2} \cdot {b}^{2}}\right) - 1 \]

      5. unpow2 N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{2} \cdot \color{blue}{\left(b \cdot b\right)}\right) - 1 \]

      6. associate-*r* N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left({b}^{2} \cdot b\right) \cdot b}\right) - 1 \]

      7. pow-plus N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      8. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{3}} \cdot b\right) - 1 \]

      9. cube-unmult N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left(b \cdot \left(b \cdot b\right)\right)} \cdot b\right) - 1 \]

      10. unpow2 N/A

          \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \left(b \cdot \color{blue}{{b}^{2}}\right) \cdot b\right) - 1 \]

      11. associate-*r* N/A

          \[\leadsto \left(\color{blue}{4 \cdot \left(b \cdot b\right)} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      12. unpow2 N/A

          \[\leadsto \left(4 \cdot \color{blue}{{b}^{2}} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      13. *-commutative N/A

          \[\leadsto \left(\color{blue}{{b}^{2} \cdot 4} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      14. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \left(b \cdot \color{blue}{\left(b \cdot b\right)}\right) \cdot b\right) - 1 \]

      15. cube-unmult N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{3}} \cdot b\right) - 1 \]

      16. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      17. pow-plus N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{\left({b}^{2} \cdot b\right)} \cdot b\right) - 1 \]

      18. associate-*r* N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{2} \cdot \left(b \cdot b\right)}\right) - 1 \]

      19. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{2} \cdot \color{blue}{{b}^{2}}\right) - 1 \]

      20. pow-sqr N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{\left(2 \cdot 2\right)}}\right) - 1 \]

      21. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{4}}\right) - 1 \]

      22. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left({b}^{2}, 4, {b}^{4}\right)} - 1 \]

      23. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      24. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      25. lower-pow.f64 99.9

          \[\leadsto \mathsf{fma}\left(b \cdot b, 4, \color{blue}{{b}^{4}}\right) - 1 \]

   5. Applied rewrites 99.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, 4, {b}^{4}\right)} - 1 \]

   6. Taylor expanded in b around 0

      \[\leadsto 4 \cdot \color{blue}{{b}^{2}} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 72.5%

      \[\leadsto \left(b \cdot b\right) \cdot \color{blue}{4} - 1 \]
3. Recombined 2 regimes into one program.

4. Final simplification 79.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -3.2 \lor \neg \left(a \leq 7.5 \cdot 10^{+26}\right):\\ \;\;\;\;\left(a \cdot a\right) \cdot \left(a \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot 4 - 1\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 82.1% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 1.5:\\ \;\;\;\;\left(a \cdot a\right) \cdot \left(a \cdot a\right) - 1\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{fma}\left(b, b, 4\right) \cdot b\right) \cdot b - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 1.5) (- (* (* a a) (* a a)) 1.0) (- (* (* (fma b b 4.0) b) b) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if (b <= 1.5) {
		tmp = ((a * a) * (a * a)) - 1.0;
	} else {
		tmp = ((fma(b, b, 4.0) * b) * b) - 1.0;
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 1.5)
		tmp = Float64(Float64(Float64(a * a) * Float64(a * a)) - 1.0);
	else
		tmp = Float64(Float64(Float64(fma(b, b, 4.0) * b) * b) - 1.0);
	end
	return tmp
end

Wolfram

code[a_, b_] := If[LessEqual[b, 1.5], N[(N[(N[(a * a), $MachinePrecision] * N[(a * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(N[(N[(b * b + 4.0), $MachinePrecision] * b), $MachinePrecision] * b), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 1.5

   1. Initial program 79.4%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4} \cdot \left(1 + \left(2 \cdot \frac{{b}^{2}}{{a}^{2}} + \left(4 \cdot \frac{1}{a} + \frac{4}{{a}^{2}}\right)\right)\right)} - 1 \]

   5. Applied rewrites 65.1%

      \[\leadsto \color{blue}{\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot {a}^{4}} - 1 \]
   6. Step-by-step derivation

   7. Applied rewrites 67.8%

      \[\leadsto \left(\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot \left(a \cdot a\right)\right) \cdot \color{blue}{\left(a \cdot a\right)} - 1 \]

   8. Taylor expanded in a around inf

      \[\leadsto {a}^{2} \cdot \left(\color{blue}{a} \cdot a\right) - 1 \]
   9. Step-by-step derivation

   10. Applied rewrites 81.0%

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

   if 1.5 < b

   1. Initial program 68.1%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + {b}^{4}\right)} - 1 \]
   4. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \left(4 \cdot \color{blue}{\left(b \cdot b\right)} + {b}^{4}\right) - 1 \]

      2. associate-*r* N/A

         \[\leadsto \left(\color{blue}{\left(4 \cdot b\right) \cdot b} + {b}^{4}\right) - 1 \]

      3. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{\left(2 \cdot 2\right)}}\right) - 1 \]

      4. pow-sqr N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{2} \cdot {b}^{2}}\right) - 1 \]

      5. unpow2 N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{2} \cdot \color{blue}{\left(b \cdot b\right)}\right) - 1 \]

      6. associate-*r* N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left({b}^{2} \cdot b\right) \cdot b}\right) - 1 \]

      7. pow-plus N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      8. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{3}} \cdot b\right) - 1 \]

      9. cube-unmult N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left(b \cdot \left(b \cdot b\right)\right)} \cdot b\right) - 1 \]

      10. unpow2 N/A

          \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \left(b \cdot \color{blue}{{b}^{2}}\right) \cdot b\right) - 1 \]

      11. associate-*r* N/A

          \[\leadsto \left(\color{blue}{4 \cdot \left(b \cdot b\right)} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      12. unpow2 N/A

          \[\leadsto \left(4 \cdot \color{blue}{{b}^{2}} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      13. *-commutative N/A

          \[\leadsto \left(\color{blue}{{b}^{2} \cdot 4} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      14. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \left(b \cdot \color{blue}{\left(b \cdot b\right)}\right) \cdot b\right) - 1 \]

      15. cube-unmult N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{3}} \cdot b\right) - 1 \]

      16. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      17. pow-plus N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{\left({b}^{2} \cdot b\right)} \cdot b\right) - 1 \]

      18. associate-*r* N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{2} \cdot \left(b \cdot b\right)}\right) - 1 \]

      19. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{2} \cdot \color{blue}{{b}^{2}}\right) - 1 \]

      20. pow-sqr N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{\left(2 \cdot 2\right)}}\right) - 1 \]

      21. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{4}}\right) - 1 \]

      22. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left({b}^{2}, 4, {b}^{4}\right)} - 1 \]

      23. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      24. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      25. lower-pow.f64 93.0

          \[\leadsto \mathsf{fma}\left(b \cdot b, 4, \color{blue}{{b}^{4}}\right) - 1 \]

   5. Applied rewrites 93.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, 4, {b}^{4}\right)} - 1 \]
   6. Step-by-step derivation

   7. Applied rewrites 93.0%

      \[\leadsto \left(b \cdot b\right) \cdot \color{blue}{\mathsf{fma}\left(b, b, 4\right)} - 1 \]
   8. Step-by-step derivation

   9. Applied rewrites 93.0%

      \[\leadsto \left(\mathsf{fma}\left(b, b, 4\right) \cdot b\right) \cdot \color{blue}{b} - 1 \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 8: 82.1% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 1.5:\\ \;\;\;\;\left(a \cdot a\right) \cdot \left(a \cdot a\right) - 1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot \mathsf{fma}\left(b, b, 4\right) - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 1.5) (- (* (* a a) (* a a)) 1.0) (- (* (* b b) (fma b b 4.0)) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if (b <= 1.5) {
		tmp = ((a * a) * (a * a)) - 1.0;
	} else {
		tmp = ((b * b) * fma(b, b, 4.0)) - 1.0;
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 1.5)
		tmp = Float64(Float64(Float64(a * a) * Float64(a * a)) - 1.0);
	else
		tmp = Float64(Float64(Float64(b * b) * fma(b, b, 4.0)) - 1.0);
	end
	return tmp
end

Wolfram

code[a_, b_] := If[LessEqual[b, 1.5], N[(N[(N[(a * a), $MachinePrecision] * N[(a * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(N[(b * b), $MachinePrecision] * N[(b * b + 4.0), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 1.5

   1. Initial program 79.4%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4} \cdot \left(1 + \left(2 \cdot \frac{{b}^{2}}{{a}^{2}} + \left(4 \cdot \frac{1}{a} + \frac{4}{{a}^{2}}\right)\right)\right)} - 1 \]

   5. Applied rewrites 65.1%

      \[\leadsto \color{blue}{\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot {a}^{4}} - 1 \]
   6. Step-by-step derivation

   7. Applied rewrites 67.8%

      \[\leadsto \left(\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot \left(a \cdot a\right)\right) \cdot \color{blue}{\left(a \cdot a\right)} - 1 \]

   8. Taylor expanded in a around inf

      \[\leadsto {a}^{2} \cdot \left(\color{blue}{a} \cdot a\right) - 1 \]
   9. Step-by-step derivation

   10. Applied rewrites 81.0%

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

   if 1.5 < b

   1. Initial program 68.1%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + {b}^{4}\right)} - 1 \]
   4. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \left(4 \cdot \color{blue}{\left(b \cdot b\right)} + {b}^{4}\right) - 1 \]

      2. associate-*r* N/A

         \[\leadsto \left(\color{blue}{\left(4 \cdot b\right) \cdot b} + {b}^{4}\right) - 1 \]

      3. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{\left(2 \cdot 2\right)}}\right) - 1 \]

      4. pow-sqr N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{2} \cdot {b}^{2}}\right) - 1 \]

      5. unpow2 N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{2} \cdot \color{blue}{\left(b \cdot b\right)}\right) - 1 \]

      6. associate-*r* N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left({b}^{2} \cdot b\right) \cdot b}\right) - 1 \]

      7. pow-plus N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      8. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{3}} \cdot b\right) - 1 \]

      9. cube-unmult N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left(b \cdot \left(b \cdot b\right)\right)} \cdot b\right) - 1 \]

      10. unpow2 N/A

          \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \left(b \cdot \color{blue}{{b}^{2}}\right) \cdot b\right) - 1 \]

      11. associate-*r* N/A

          \[\leadsto \left(\color{blue}{4 \cdot \left(b \cdot b\right)} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      12. unpow2 N/A

          \[\leadsto \left(4 \cdot \color{blue}{{b}^{2}} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      13. *-commutative N/A

          \[\leadsto \left(\color{blue}{{b}^{2} \cdot 4} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      14. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \left(b \cdot \color{blue}{\left(b \cdot b\right)}\right) \cdot b\right) - 1 \]

      15. cube-unmult N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{3}} \cdot b\right) - 1 \]

      16. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      17. pow-plus N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{\left({b}^{2} \cdot b\right)} \cdot b\right) - 1 \]

      18. associate-*r* N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{2} \cdot \left(b \cdot b\right)}\right) - 1 \]

      19. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{2} \cdot \color{blue}{{b}^{2}}\right) - 1 \]

      20. pow-sqr N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{\left(2 \cdot 2\right)}}\right) - 1 \]

      21. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{4}}\right) - 1 \]

      22. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left({b}^{2}, 4, {b}^{4}\right)} - 1 \]

      23. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      24. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      25. lower-pow.f64 93.0

          \[\leadsto \mathsf{fma}\left(b \cdot b, 4, \color{blue}{{b}^{4}}\right) - 1 \]

   5. Applied rewrites 93.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, 4, {b}^{4}\right)} - 1 \]
   6. Step-by-step derivation

   7. Applied rewrites 93.0%

      \[\leadsto \left(b \cdot b\right) \cdot \color{blue}{\mathsf{fma}\left(b, b, 4\right)} - 1 \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 9: 77.5% accurate, 6.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 6.7 \cdot 10^{+153}:\\ \;\;\;\;\left(a \cdot a\right) \cdot \left(a \cdot a\right) - 1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot 4 - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 6.7e+153) (- (* (* a a) (* a a)) 1.0) (- (* (* b b) 4.0) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if (b <= 6.7e+153) {
		tmp = ((a * a) * (a * a)) - 1.0;
	} else {
		tmp = ((b * b) * 4.0) - 1.0;
	}
	return tmp;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(a, b)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8) :: tmp
    if (b <= 6.7d+153) then
        tmp = ((a * a) * (a * a)) - 1.0d0
    else
        tmp = ((b * b) * 4.0d0) - 1.0d0
    end if
    code = tmp
end function

Java

public static double code(double a, double b) {
	double tmp;
	if (b <= 6.7e+153) {
		tmp = ((a * a) * (a * a)) - 1.0;
	} else {
		tmp = ((b * b) * 4.0) - 1.0;
	}
	return tmp;
}

Python

def code(a, b):
	tmp = 0
	if b <= 6.7e+153:
		tmp = ((a * a) * (a * a)) - 1.0
	else:
		tmp = ((b * b) * 4.0) - 1.0
	return tmp

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 6.7e+153)
		tmp = Float64(Float64(Float64(a * a) * Float64(a * a)) - 1.0);
	else
		tmp = Float64(Float64(Float64(b * b) * 4.0) - 1.0);
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b)
	tmp = 0.0;
	if (b <= 6.7e+153)
		tmp = ((a * a) * (a * a)) - 1.0;
	else
		tmp = ((b * b) * 4.0) - 1.0;
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_] := If[LessEqual[b, 6.7e+153], N[(N[(N[(a * a), $MachinePrecision] * N[(a * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(N[(b * b), $MachinePrecision] * 4.0), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 6.70000000000000005e153

   1. Initial program 78.9%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf

      \[\leadsto \color{blue}{{a}^{4} \cdot \left(1 + \left(2 \cdot \frac{{b}^{2}}{{a}^{2}} + \left(4 \cdot \frac{1}{a} + \frac{4}{{a}^{2}}\right)\right)\right)} - 1 \]

   5. Applied rewrites 60.1%

      \[\leadsto \color{blue}{\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot {a}^{4}} - 1 \]
   6. Step-by-step derivation

   7. Applied rewrites 63.6%

      \[\leadsto \left(\left(1 - \frac{\frac{\mathsf{fma}\left(-2, b \cdot b, -4\right)}{a} - 4}{a}\right) \cdot \left(a \cdot a\right)\right) \cdot \color{blue}{\left(a \cdot a\right)} - 1 \]

   8. Taylor expanded in a around inf

      \[\leadsto {a}^{2} \cdot \left(\color{blue}{a} \cdot a\right) - 1 \]
   9. Step-by-step derivation

   10. Applied rewrites 71.9%

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

   if 6.70000000000000005e153 < b

   1. Initial program 55.6%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + {b}^{4}\right)} - 1 \]
   4. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \left(4 \cdot \color{blue}{\left(b \cdot b\right)} + {b}^{4}\right) - 1 \]

      2. associate-*r* N/A

         \[\leadsto \left(\color{blue}{\left(4 \cdot b\right) \cdot b} + {b}^{4}\right) - 1 \]

      3. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{\left(2 \cdot 2\right)}}\right) - 1 \]

      4. pow-sqr N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{2} \cdot {b}^{2}}\right) - 1 \]

      5. unpow2 N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{2} \cdot \color{blue}{\left(b \cdot b\right)}\right) - 1 \]

      6. associate-*r* N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left({b}^{2} \cdot b\right) \cdot b}\right) - 1 \]

      7. pow-plus N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      8. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{3}} \cdot b\right) - 1 \]

      9. cube-unmult N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left(b \cdot \left(b \cdot b\right)\right)} \cdot b\right) - 1 \]

      10. unpow2 N/A

          \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \left(b \cdot \color{blue}{{b}^{2}}\right) \cdot b\right) - 1 \]

      11. associate-*r* N/A

          \[\leadsto \left(\color{blue}{4 \cdot \left(b \cdot b\right)} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      12. unpow2 N/A

          \[\leadsto \left(4 \cdot \color{blue}{{b}^{2}} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      13. *-commutative N/A

          \[\leadsto \left(\color{blue}{{b}^{2} \cdot 4} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      14. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \left(b \cdot \color{blue}{\left(b \cdot b\right)}\right) \cdot b\right) - 1 \]

      15. cube-unmult N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{3}} \cdot b\right) - 1 \]

      16. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      17. pow-plus N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{\left({b}^{2} \cdot b\right)} \cdot b\right) - 1 \]

      18. associate-*r* N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{2} \cdot \left(b \cdot b\right)}\right) - 1 \]

      19. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{2} \cdot \color{blue}{{b}^{2}}\right) - 1 \]

      20. pow-sqr N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{\left(2 \cdot 2\right)}}\right) - 1 \]

      21. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{4}}\right) - 1 \]

      22. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left({b}^{2}, 4, {b}^{4}\right)} - 1 \]

      23. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      24. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      25. lower-pow.f64 100.0

          \[\leadsto \mathsf{fma}\left(b \cdot b, 4, \color{blue}{{b}^{4}}\right) - 1 \]

   5. Applied rewrites 100.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, 4, {b}^{4}\right)} - 1 \]

   6. Taylor expanded in b around 0

      \[\leadsto 4 \cdot \color{blue}{{b}^{2}} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 100.0%

      \[\leadsto \left(b \cdot b\right) \cdot \color{blue}{4} - 1 \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 10: 61.4% accurate, 8.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 6.5 \cdot 10^{+153}:\\ \;\;\;\;\left(a \cdot a\right) \cdot 4 - 1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot 4 - 1\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 6.5e+153) (- (* (* a a) 4.0) 1.0) (- (* (* b b) 4.0) 1.0)))

C

double code(double a, double b) {
	double tmp;
	if (b <= 6.5e+153) {
		tmp = ((a * a) * 4.0) - 1.0;
	} else {
		tmp = ((b * b) * 4.0) - 1.0;
	}
	return tmp;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(a, b)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8) :: tmp
    if (b <= 6.5d+153) then
        tmp = ((a * a) * 4.0d0) - 1.0d0
    else
        tmp = ((b * b) * 4.0d0) - 1.0d0
    end if
    code = tmp
end function

Java

public static double code(double a, double b) {
	double tmp;
	if (b <= 6.5e+153) {
		tmp = ((a * a) * 4.0) - 1.0;
	} else {
		tmp = ((b * b) * 4.0) - 1.0;
	}
	return tmp;
}

Python

def code(a, b):
	tmp = 0
	if b <= 6.5e+153:
		tmp = ((a * a) * 4.0) - 1.0
	else:
		tmp = ((b * b) * 4.0) - 1.0
	return tmp

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 6.5e+153)
		tmp = Float64(Float64(Float64(a * a) * 4.0) - 1.0);
	else
		tmp = Float64(Float64(Float64(b * b) * 4.0) - 1.0);
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b)
	tmp = 0.0;
	if (b <= 6.5e+153)
		tmp = ((a * a) * 4.0) - 1.0;
	else
		tmp = ((b * b) * 4.0) - 1.0;
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_] := If[LessEqual[b, 6.5e+153], N[(N[(N[(a * a), $MachinePrecision] * 4.0), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(N[(b * b), $MachinePrecision] * 4.0), $MachinePrecision] - 1.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 6.49999999999999972e153

   1. Initial program 78.9%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + \left(a \cdot \left(-12 \cdot {b}^{2} + a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right) + {b}^{4}\right)\right)} - 1 \]
   4. Step-by-step derivation

      1. +-commutative N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \color{blue}{\left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2} + a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right) - 1 \]

      2. distribute-lft-in N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \left({b}^{4} + \color{blue}{\left(a \cdot \left(-12 \cdot {b}^{2}\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right)\right) - 1 \]

      3. associate-+r+ N/A

         \[\leadsto \left(4 \cdot {b}^{2} + \color{blue}{\left(\left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2}\right)\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)}\right) - 1 \]

      4. associate-+r+ N/A

         \[\leadsto \color{blue}{\left(\left(4 \cdot {b}^{2} + \left({b}^{4} + a \cdot \left(-12 \cdot {b}^{2}\right)\right)\right) + a \cdot \left(a \cdot \left(4 + 2 \cdot {b}^{2}\right)\right)\right)} - 1 \]

   5. Applied rewrites 85.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, \mathsf{fma}\left(b, b, \mathsf{fma}\left(-12, a, 4\right)\right), \left(\mathsf{fma}\left(b \cdot b, 2, 4\right) \cdot a\right) \cdot a\right)} - 1 \]

   6. Taylor expanded in b around 0

      \[\leadsto 4 \cdot \color{blue}{{a}^{2}} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 54.9%

      \[\leadsto \left(a \cdot a\right) \cdot \color{blue}{4} - 1 \]

   if 6.49999999999999972e153 < b

   1. Initial program 55.6%

      \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
   2. Add Preprocessing

   3. Taylor expanded in a around 0

      \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + {b}^{4}\right)} - 1 \]
   4. Step-by-step derivation

      1. unpow2 N/A

         \[\leadsto \left(4 \cdot \color{blue}{\left(b \cdot b\right)} + {b}^{4}\right) - 1 \]

      2. associate-*r* N/A

         \[\leadsto \left(\color{blue}{\left(4 \cdot b\right) \cdot b} + {b}^{4}\right) - 1 \]

      3. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{\left(2 \cdot 2\right)}}\right) - 1 \]

      4. pow-sqr N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{2} \cdot {b}^{2}}\right) - 1 \]

      5. unpow2 N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{2} \cdot \color{blue}{\left(b \cdot b\right)}\right) - 1 \]

      6. associate-*r* N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left({b}^{2} \cdot b\right) \cdot b}\right) - 1 \]

      7. pow-plus N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      8. metadata-eval N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{3}} \cdot b\right) - 1 \]

      9. cube-unmult N/A

         \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left(b \cdot \left(b \cdot b\right)\right)} \cdot b\right) - 1 \]

      10. unpow2 N/A

          \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \left(b \cdot \color{blue}{{b}^{2}}\right) \cdot b\right) - 1 \]

      11. associate-*r* N/A

          \[\leadsto \left(\color{blue}{4 \cdot \left(b \cdot b\right)} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      12. unpow2 N/A

          \[\leadsto \left(4 \cdot \color{blue}{{b}^{2}} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      13. *-commutative N/A

          \[\leadsto \left(\color{blue}{{b}^{2} \cdot 4} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

      14. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \left(b \cdot \color{blue}{\left(b \cdot b\right)}\right) \cdot b\right) - 1 \]

      15. cube-unmult N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{3}} \cdot b\right) - 1 \]

      16. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{\left(2 + 1\right)}} \cdot b\right) - 1 \]

      17. pow-plus N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{\left({b}^{2} \cdot b\right)} \cdot b\right) - 1 \]

      18. associate-*r* N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{2} \cdot \left(b \cdot b\right)}\right) - 1 \]

      19. unpow2 N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{2} \cdot \color{blue}{{b}^{2}}\right) - 1 \]

      20. pow-sqr N/A

          \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{\left(2 \cdot 2\right)}}\right) - 1 \]

      21. metadata-eval N/A

          \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{4}}\right) - 1 \]

      22. lower-fma.f64 N/A

          \[\leadsto \color{blue}{\mathsf{fma}\left({b}^{2}, 4, {b}^{4}\right)} - 1 \]

      23. unpow2 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      24. lower-*.f64 N/A

          \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

      25. lower-pow.f64 100.0

          \[\leadsto \mathsf{fma}\left(b \cdot b, 4, \color{blue}{{b}^{4}}\right) - 1 \]

   5. Applied rewrites 100.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, 4, {b}^{4}\right)} - 1 \]

   6. Taylor expanded in b around 0

      \[\leadsto 4 \cdot \color{blue}{{b}^{2}} - 1 \]
   7. Step-by-step derivation

   8. Applied rewrites 100.0%

      \[\leadsto \left(b \cdot b\right) \cdot \color{blue}{4} - 1 \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 11: 51.7% accurate, 11.4× speedup

Math

\[\begin{array}{l} \\ \left(b \cdot b\right) \cdot 4 - 1 \end{array} \]

FPCore

(FPCore (a b) :precision binary64 (- (* (* b b) 4.0) 1.0))

C

double code(double a, double b) {
	return ((b * b) * 4.0) - 1.0;
}

Fortran

module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(a, b)
use fmin_fmax_functions
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    code = ((b * b) * 4.0d0) - 1.0d0
end function

Java

public static double code(double a, double b) {
	return ((b * b) * 4.0) - 1.0;
}

Python

def code(a, b):
	return ((b * b) * 4.0) - 1.0

Julia

function code(a, b)
	return Float64(Float64(Float64(b * b) * 4.0) - 1.0)
end

MATLAB

function tmp = code(a, b)
	tmp = ((b * b) * 4.0) - 1.0;
end

Wolfram

code[a_, b_] := N[(N[(N[(b * b), $MachinePrecision] * 4.0), $MachinePrecision] - 1.0), $MachinePrecision]

Derivation

1. Initial program 76.4%

   \[\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \]
2. Add Preprocessing

3. Taylor expanded in a around 0

   \[\leadsto \color{blue}{\left(4 \cdot {b}^{2} + {b}^{4}\right)} - 1 \]
4. Step-by-step derivation

   1. unpow2 N/A

      \[\leadsto \left(4 \cdot \color{blue}{\left(b \cdot b\right)} + {b}^{4}\right) - 1 \]

   2. associate-*r* N/A

      \[\leadsto \left(\color{blue}{\left(4 \cdot b\right) \cdot b} + {b}^{4}\right) - 1 \]

   3. metadata-eval N/A

      \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{\left(2 \cdot 2\right)}}\right) - 1 \]

   4. pow-sqr N/A

      \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{2} \cdot {b}^{2}}\right) - 1 \]

   5. unpow2 N/A

      \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{2} \cdot \color{blue}{\left(b \cdot b\right)}\right) - 1 \]

   6. associate-*r* N/A

      \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left({b}^{2} \cdot b\right) \cdot b}\right) - 1 \]

   7. pow-plus N/A

      \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{{b}^{\left(2 + 1\right)}} \cdot b\right) - 1 \]

   8. metadata-eval N/A

      \[\leadsto \left(\left(4 \cdot b\right) \cdot b + {b}^{\color{blue}{3}} \cdot b\right) - 1 \]

   9. cube-unmult N/A

      \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \color{blue}{\left(b \cdot \left(b \cdot b\right)\right)} \cdot b\right) - 1 \]

   10. unpow2 N/A

       \[\leadsto \left(\left(4 \cdot b\right) \cdot b + \left(b \cdot \color{blue}{{b}^{2}}\right) \cdot b\right) - 1 \]

   11. associate-*r* N/A

       \[\leadsto \left(\color{blue}{4 \cdot \left(b \cdot b\right)} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

   12. unpow2 N/A

       \[\leadsto \left(4 \cdot \color{blue}{{b}^{2}} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

   13. *-commutative N/A

       \[\leadsto \left(\color{blue}{{b}^{2} \cdot 4} + \left(b \cdot {b}^{2}\right) \cdot b\right) - 1 \]

   14. unpow2 N/A

       \[\leadsto \left({b}^{2} \cdot 4 + \left(b \cdot \color{blue}{\left(b \cdot b\right)}\right) \cdot b\right) - 1 \]

   15. cube-unmult N/A

       \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{3}} \cdot b\right) - 1 \]

   16. metadata-eval N/A

       \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{\left(2 + 1\right)}} \cdot b\right) - 1 \]

   17. pow-plus N/A

       \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{\left({b}^{2} \cdot b\right)} \cdot b\right) - 1 \]

   18. associate-*r* N/A

       \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{2} \cdot \left(b \cdot b\right)}\right) - 1 \]

   19. unpow2 N/A

       \[\leadsto \left({b}^{2} \cdot 4 + {b}^{2} \cdot \color{blue}{{b}^{2}}\right) - 1 \]

   20. pow-sqr N/A

       \[\leadsto \left({b}^{2} \cdot 4 + \color{blue}{{b}^{\left(2 \cdot 2\right)}}\right) - 1 \]

   21. metadata-eval N/A

       \[\leadsto \left({b}^{2} \cdot 4 + {b}^{\color{blue}{4}}\right) - 1 \]

   22. lower-fma.f64 N/A

       \[\leadsto \color{blue}{\mathsf{fma}\left({b}^{2}, 4, {b}^{4}\right)} - 1 \]

   23. unpow2 N/A

       \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

   24. lower-*.f64 N/A

       \[\leadsto \mathsf{fma}\left(\color{blue}{b \cdot b}, 4, {b}^{4}\right) - 1 \]

   25. lower-pow.f64 75.0

       \[\leadsto \mathsf{fma}\left(b \cdot b, 4, \color{blue}{{b}^{4}}\right) - 1 \]

5. Applied rewrites 75.0%

   \[\leadsto \color{blue}{\mathsf{fma}\left(b \cdot b, 4, {b}^{4}\right)} - 1 \]

6. Taylor expanded in b around 0

   \[\leadsto 4 \cdot \color{blue}{{b}^{2}} - 1 \]
7. Step-by-step derivation

8. Applied rewrites 53.3%

   \[\leadsto \left(b \cdot b\right) \cdot \color{blue}{4} - 1 \]
9. Add Preprocessing

Reproduce

herbie shell --seed 2024350 
(FPCore (a b)
  :name "Bouland and Aaronson, Equation (25)"
  :precision binary64
  (- (+ (pow (+ (* a a) (* b b)) 2.0) (* 4.0 (+ (* (* a a) (+ 1.0 a)) (* (* b b) (- 1.0 (* 3.0 a)))))) 1.0))