Bouland and Aaronson, Equation (25)

Percentage Accurate: 73.9% → 99.2%

Time: 4.5s

Alternatives: 9

Speedup: 6.4×

• 60.5% 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: 73.9% 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: 99.2% accurate, 3.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(b, b, a \cdot a\right)\\ \mathsf{fma}\left(t\_0, t\_0, \left(b \cdot b\right) \cdot 4 - 1\right) \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (let* ((t_0 (fma b b (* a a)))) (fma t_0 t_0 (- (* (* b b) 4.0) 1.0))))

C

double code(double a, double b) {
	double t_0 = fma(b, b, (a * a));
	return fma(t_0, t_0, (((b * b) * 4.0) - 1.0));
}

Julia

function code(a, b)
	t_0 = fma(b, b, Float64(a * a))
	return fma(t_0, t_0, Float64(Float64(Float64(b * b) * 4.0) - 1.0))
end

Wolfram

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

Derivation

1. Initial program 73.9%

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

3. Applied rewrites 75.2%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(b, b, a \cdot a\right), \mathsf{fma}\left(b, b, a \cdot a\right), \mathsf{fma}\left(a \cdot a, 1 + a, \left(b \cdot b\right) \cdot \mathsf{fma}\left(-3, a, 1\right)\right) \cdot 4 - 1\right)} \]

4. Taylor expanded in a around 0

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

   1. pow2 N/A

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

   2. lift-*.f64 99.2

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

6. Applied rewrites 99.2%

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

Alternative 2: 69.6% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\left({\left(a \cdot a + b \cdot b\right)}^{2} + 4 \cdot \left(\left(a \cdot a\right) \cdot \left(1 + a\right) + \left(b \cdot b\right) \cdot \left(1 - 3 \cdot a\right)\right)\right) - 1 \leq -0.5:\\ \;\;\;\;\left(a \cdot a\right) \cdot 4 - 1\\ \mathbf{else}:\\ \;\;\;\;\left(a \cdot a\right) \cdot \left(a \cdot a\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<=
      (-
       (+
        (pow (+ (* a a) (* b b)) 2.0)
        (* 4.0 (+ (* (* a a) (+ 1.0 a)) (* (* b b) (- 1.0 (* 3.0 a))))))
       1.0)
      -0.5)
   (- (* (* a a) 4.0) 1.0)
   (* (* a a) (* a a))))

C

double code(double a, double b) {
	double tmp;
	if (((pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0) <= -0.5) {
		tmp = ((a * a) * 4.0) - 1.0;
	} else {
		tmp = (a * a) * (a * a);
	}
	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 * a) + (b * b)) ** 2.0d0) + (4.0d0 * (((a * a) * (1.0d0 + a)) + ((b * b) * (1.0d0 - (3.0d0 * a)))))) - 1.0d0) <= (-0.5d0)) then
        tmp = ((a * a) * 4.0d0) - 1.0d0
    else
        tmp = (a * a) * (a * a)
    end if
    code = tmp
end function

Java

public static double code(double a, double b) {
	double tmp;
	if (((Math.pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0) <= -0.5) {
		tmp = ((a * a) * 4.0) - 1.0;
	} else {
		tmp = (a * a) * (a * a);
	}
	return tmp;
}

Python

def code(a, b):
	tmp = 0
	if ((math.pow(((a * a) + (b * b)), 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0) <= -0.5:
		tmp = ((a * a) * 4.0) - 1.0
	else:
		tmp = (a * a) * (a * a)
	return tmp

Julia

function code(a, b)
	tmp = 0.0
	if (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) <= -0.5)
		tmp = Float64(Float64(Float64(a * a) * 4.0) - 1.0);
	else
		tmp = Float64(Float64(a * a) * Float64(a * a));
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b)
	tmp = 0.0;
	if ((((((a * a) + (b * b)) ^ 2.0) + (4.0 * (((a * a) * (1.0 + a)) + ((b * b) * (1.0 - (3.0 * a)))))) - 1.0) <= -0.5)
		tmp = ((a * a) * 4.0) - 1.0;
	else
		tmp = (a * a) * (a * a);
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_] := If[LessEqual[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], -0.5], N[(N[(N[(a * a), $MachinePrecision] * 4.0), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(a * a), $MachinePrecision] * N[(a * a), $MachinePrecision]), $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)) < -0.5

   1. Initial program 100.0%

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

   2. Taylor expanded in a around -inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

   4. Applied rewrites 49.9%

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

   5. Taylor expanded in a around 0

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

      1. lower-*.f64 N/A

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

      2. pow2 N/A

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

      3. lift-*.f64 N/A

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

      4. *-commutative N/A

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

      5. pow2 N/A

         \[\leadsto \left(a \cdot a\right) \cdot \left(4 + \left(b \cdot b\right) \cdot 2\right) - 1 \]

      6. +-commutative N/A

         \[\leadsto \left(a \cdot a\right) \cdot \left(\left(b \cdot b\right) \cdot 2 + 4\right) - 1 \]

      7. lift-fma.f64 N/A

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

      8. lift-*.f64 98.6

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

   7. Applied rewrites 98.6%

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

   8. Taylor expanded in b around 0

      \[\leadsto \left(a \cdot a\right) \cdot 4 - 1 \]
   9. Step-by-step derivation

   10. Applied rewrites 98.6%

       \[\leadsto \left(a \cdot a\right) \cdot 4 - 1 \]

   if -0.5 < (-.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 65.1%

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

   2. Taylor expanded in a around inf

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

      1. lower-pow.f64 60.0

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

   4. Applied rewrites 60.0%

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

      1. lift-pow.f64 N/A

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

      2. metadata-eval N/A

         \[\leadsto {a}^{\left(2 + \color{blue}{2}\right)} \]

      3. pow-prod-up N/A

         \[\leadsto {a}^{2} \cdot \color{blue}{{a}^{2}} \]

      4. lower-*.f64 N/A

         \[\leadsto {a}^{2} \cdot \color{blue}{{a}^{2}} \]

      5. pow2 N/A

         \[\leadsto \left(a \cdot a\right) \cdot {\color{blue}{a}}^{2} \]

      6. lift-*.f64 N/A

         \[\leadsto \left(a \cdot a\right) \cdot {\color{blue}{a}}^{2} \]

      7. pow2 N/A

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

      8. lift-*.f64 59.9

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

   6. Applied rewrites 59.9%

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

Alternative 3: 88.3% accurate, 3.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 18500000000:\\ \;\;\;\;\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot \left(a \cdot a\right) - 1\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\mathsf{fma}\left(b, b, a \cdot a\right), b \cdot b, \left(b \cdot b\right) \cdot 4 - 1\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 18500000000.0)
   (- (* (fma (+ 4.0 a) a (fma (* b b) 2.0 4.0)) (* a a)) 1.0)
   (fma (fma b b (* a a)) (* b b) (- (* (* b b) 4.0) 1.0))))

C

double code(double a, double b) {
	double tmp;
	if (b <= 18500000000.0) {
		tmp = (fma((4.0 + a), a, fma((b * b), 2.0, 4.0)) * (a * a)) - 1.0;
	} else {
		tmp = fma(fma(b, b, (a * a)), (b * b), (((b * b) * 4.0) - 1.0));
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 18500000000.0)
		tmp = Float64(Float64(fma(Float64(4.0 + a), a, fma(Float64(b * b), 2.0, 4.0)) * Float64(a * a)) - 1.0);
	else
		tmp = fma(fma(b, b, Float64(a * a)), Float64(b * b), Float64(Float64(Float64(b * b) * 4.0) - 1.0));
	end
	return tmp
end

Wolfram

code[a_, b_] := If[LessEqual[b, 18500000000.0], N[(N[(N[(N[(4.0 + a), $MachinePrecision] * a + N[(N[(b * b), $MachinePrecision] * 2.0 + 4.0), $MachinePrecision]), $MachinePrecision] * N[(a * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(b * b + N[(a * a), $MachinePrecision]), $MachinePrecision] * N[(b * b), $MachinePrecision] + N[(N[(N[(b * b), $MachinePrecision] * 4.0), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 1.85e10

   1. Initial program 77.0%

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

   2. Taylor expanded in a around -inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

   4. Applied rewrites 68.0%

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

   5. Taylor expanded in a around 0

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. +-commutative N/A

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

      4. lower-+.f64 N/A

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

      5. +-commutative N/A

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

      6. *-commutative N/A

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

      7. lower-fma.f64 N/A

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

      8. lower-+.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 N/A

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

      11. pow2 N/A

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

      12. lift-*.f64 N/A

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

      13. pow2 N/A

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

      14. lift-*.f64 85.5

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

   7. Applied rewrites 85.5%

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

      1. lift-+.f64 N/A

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

      2. lift-+.f64 N/A

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

      3. lift-fma.f64 N/A

         \[\leadsto \left(\left(\left(4 + a\right) \cdot a + \left(b \cdot b\right) \cdot 2\right) + 4\right) \cdot \left(a \cdot a\right) - 1 \]

      4. associate-+r+ N/A

         \[\leadsto \left(\left(4 + a\right) \cdot a + \left(\left(b \cdot b\right) \cdot 2 + 4\right)\right) \cdot \left(a \cdot a\right) - 1 \]

      5. lift-*.f64 N/A

         \[\leadsto \left(\left(4 + a\right) \cdot a + \left(\left(b \cdot b\right) \cdot 2 + 4\right)\right) \cdot \left(a \cdot a\right) - 1 \]

      6. lift-fma.f64 N/A

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

      7. lift-fma.f64 N/A

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

      8. lift-+.f64 85.5

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

   9. Applied rewrites 85.5%

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

   if 1.85e10 < b

   1. Initial program 63.9%

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

   3. Applied rewrites 66.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(b, b, a \cdot a\right), \mathsf{fma}\left(b, b, a \cdot a\right), \mathsf{fma}\left(a \cdot a, 1 + a, \left(b \cdot b\right) \cdot \mathsf{fma}\left(-3, a, 1\right)\right) \cdot 4 - 1\right)} \]

   4. Taylor expanded in a around 0

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

      1. pow2 N/A

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

      2. lift-*.f64 99.9

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

   6. Applied rewrites 99.9%

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

   7. Taylor expanded in a around 0

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

      1. pow2 N/A

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

      2. lift-*.f64 97.4

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

   9. Applied rewrites 97.4%

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

Alternative 4: 85.9% accurate, 4.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 5.7 \cdot 10^{+76}:\\ \;\;\;\;\mathsf{fma}\left(4 + a, a, \mathsf{fma}\left(b \cdot b, 2, 4\right)\right) \cdot \left(a \cdot a\right) - 1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot \left(b \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 5.7e+76)
   (- (* (fma (+ 4.0 a) a (fma (* b b) 2.0 4.0)) (* a a)) 1.0)
   (* (* b b) (* b b))))

C

double code(double a, double b) {
	double tmp;
	if (b <= 5.7e+76) {
		tmp = (fma((4.0 + a), a, fma((b * b), 2.0, 4.0)) * (a * a)) - 1.0;
	} else {
		tmp = (b * b) * (b * b);
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 5.7e+76)
		tmp = Float64(Float64(fma(Float64(4.0 + a), a, fma(Float64(b * b), 2.0, 4.0)) * Float64(a * a)) - 1.0);
	else
		tmp = Float64(Float64(b * b) * Float64(b * b));
	end
	return tmp
end

Wolfram

code[a_, b_] := If[LessEqual[b, 5.7e+76], N[(N[(N[(N[(4.0 + a), $MachinePrecision] * a + N[(N[(b * b), $MachinePrecision] * 2.0 + 4.0), $MachinePrecision]), $MachinePrecision] * N[(a * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(b * b), $MachinePrecision] * N[(b * b), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 5.70000000000000004e76

   1. Initial program 76.9%

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

   2. Taylor expanded in a around -inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

   4. Applied rewrites 66.5%

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

   5. Taylor expanded in a around 0

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. +-commutative N/A

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

      4. lower-+.f64 N/A

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

      5. +-commutative N/A

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

      6. *-commutative N/A

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

      7. lower-fma.f64 N/A

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

      8. lower-+.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 N/A

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

      11. pow2 N/A

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

      12. lift-*.f64 N/A

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

      13. pow2 N/A

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

      14. lift-*.f64 82.8

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

   7. Applied rewrites 82.8%

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

      1. lift-+.f64 N/A

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

      2. lift-+.f64 N/A

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

      3. lift-fma.f64 N/A

         \[\leadsto \left(\left(\left(4 + a\right) \cdot a + \left(b \cdot b\right) \cdot 2\right) + 4\right) \cdot \left(a \cdot a\right) - 1 \]

      4. associate-+r+ N/A

         \[\leadsto \left(\left(4 + a\right) \cdot a + \left(\left(b \cdot b\right) \cdot 2 + 4\right)\right) \cdot \left(a \cdot a\right) - 1 \]

      5. lift-*.f64 N/A

         \[\leadsto \left(\left(4 + a\right) \cdot a + \left(\left(b \cdot b\right) \cdot 2 + 4\right)\right) \cdot \left(a \cdot a\right) - 1 \]

      6. lift-fma.f64 N/A

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

      7. lift-fma.f64 N/A

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

      8. lift-+.f64 82.8

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

   9. Applied rewrites 82.8%

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

   if 5.70000000000000004e76 < b

   1. Initial program 60.3%

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

   2. Taylor expanded in b around inf

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

      1. lower-pow.f64 99.9

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

   4. Applied rewrites 99.9%

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

      1. lift-pow.f64 N/A

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

      2. metadata-eval N/A

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

      3. pow-prod-up N/A

         \[\leadsto {b}^{2} \cdot \color{blue}{{b}^{2}} \]

      4. lower-*.f64 N/A

         \[\leadsto {b}^{2} \cdot \color{blue}{{b}^{2}} \]

      5. pow2 N/A

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

      6. lift-*.f64 N/A

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

      7. pow2 N/A

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

      8. lift-*.f64 99.9

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

   6. Applied rewrites 99.9%

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

Alternative 5: 81.1% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 5.7 \cdot 10^{+76}:\\ \;\;\;\;\mathsf{fma}\left(4 + a, a, 4\right) \cdot \left(a \cdot a\right) - 1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot \left(b \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 5.7e+76)
   (- (* (fma (+ 4.0 a) a 4.0) (* a a)) 1.0)
   (* (* b b) (* b b))))

C

double code(double a, double b) {
	double tmp;
	if (b <= 5.7e+76) {
		tmp = (fma((4.0 + a), a, 4.0) * (a * a)) - 1.0;
	} else {
		tmp = (b * b) * (b * b);
	}
	return tmp;
}

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 5.7e+76)
		tmp = Float64(Float64(fma(Float64(4.0 + a), a, 4.0) * Float64(a * a)) - 1.0);
	else
		tmp = Float64(Float64(b * b) * Float64(b * b));
	end
	return tmp
end

Wolfram

code[a_, b_] := If[LessEqual[b, 5.7e+76], N[(N[(N[(N[(4.0 + a), $MachinePrecision] * a + 4.0), $MachinePrecision] * N[(a * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(b * b), $MachinePrecision] * N[(b * b), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 5.70000000000000004e76

   1. Initial program 76.9%

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

   2. Taylor expanded in a around -inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

   4. Applied rewrites 66.5%

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

   5. Taylor expanded in a around 0

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. +-commutative N/A

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

      4. lower-+.f64 N/A

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

      5. +-commutative N/A

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

      6. *-commutative N/A

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

      7. lower-fma.f64 N/A

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

      8. lower-+.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 N/A

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

      11. pow2 N/A

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

      12. lift-*.f64 N/A

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

      13. pow2 N/A

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

      14. lift-*.f64 82.8

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

   7. Applied rewrites 82.8%

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

   8. Taylor expanded in b around 0

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. +-commutative N/A

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

      4. *-commutative N/A

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

      5. lift-fma.f64 N/A

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

      6. lift-+.f64 N/A

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

      7. pow2 N/A

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

      8. lift-*.f64 77.0

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

   10. Applied rewrites 77.0%

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

   if 5.70000000000000004e76 < b

   1. Initial program 60.3%

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

   2. Taylor expanded in b around inf

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

      1. lower-pow.f64 99.9

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

   4. Applied rewrites 99.9%

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

      1. lift-pow.f64 N/A

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

      2. metadata-eval N/A

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

      3. pow-prod-up N/A

         \[\leadsto {b}^{2} \cdot \color{blue}{{b}^{2}} \]

      4. lower-*.f64 N/A

         \[\leadsto {b}^{2} \cdot \color{blue}{{b}^{2}} \]

      5. pow2 N/A

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

      6. lift-*.f64 N/A

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

      7. pow2 N/A

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

      8. lift-*.f64 99.9

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

   6. Applied rewrites 99.9%

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

Alternative 6: 80.4% accurate, 6.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 5.7 \cdot 10^{+76}:\\ \;\;\;\;\left(a \cdot a\right) \cdot \left(a \cdot a\right) - 1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot \left(b \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 5.7e+76) (- (* (* a a) (* a a)) 1.0) (* (* b b) (* b b))))

C

double code(double a, double b) {
	double tmp;
	if (b <= 5.7e+76) {
		tmp = ((a * a) * (a * a)) - 1.0;
	} else {
		tmp = (b * b) * (b * b);
	}
	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 <= 5.7d+76) then
        tmp = ((a * a) * (a * a)) - 1.0d0
    else
        tmp = (b * b) * (b * b)
    end if
    code = tmp
end function

Java

public static double code(double a, double b) {
	double tmp;
	if (b <= 5.7e+76) {
		tmp = ((a * a) * (a * a)) - 1.0;
	} else {
		tmp = (b * b) * (b * b);
	}
	return tmp;
}

Python

def code(a, b):
	tmp = 0
	if b <= 5.7e+76:
		tmp = ((a * a) * (a * a)) - 1.0
	else:
		tmp = (b * b) * (b * b)
	return tmp

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 5.7e+76)
		tmp = Float64(Float64(Float64(a * a) * Float64(a * a)) - 1.0);
	else
		tmp = Float64(Float64(b * b) * Float64(b * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b)
	tmp = 0.0;
	if (b <= 5.7e+76)
		tmp = ((a * a) * (a * a)) - 1.0;
	else
		tmp = (b * b) * (b * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_] := If[LessEqual[b, 5.7e+76], N[(N[(N[(a * a), $MachinePrecision] * N[(a * a), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(b * b), $MachinePrecision] * N[(b * b), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 5.70000000000000004e76

   1. Initial program 76.9%

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

   2. Taylor expanded in a around -inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

   4. Applied rewrites 66.5%

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

   5. Taylor expanded in a around 0

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

      3. +-commutative N/A

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

      4. lower-+.f64 N/A

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

      5. +-commutative N/A

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

      6. *-commutative N/A

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

      7. lower-fma.f64 N/A

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

      8. lower-+.f64 N/A

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

      9. *-commutative N/A

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

      10. lower-*.f64 N/A

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

      11. pow2 N/A

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

      12. lift-*.f64 N/A

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

      13. pow2 N/A

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

      14. lift-*.f64 82.8

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

   7. Applied rewrites 82.8%

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

   8. Taylor expanded in a around inf

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

      1. pow2 N/A

         \[\leadsto \left(a \cdot a\right) \cdot \left(a \cdot a\right) - 1 \]

      2. lift-*.f64 76.1

         \[\leadsto \left(a \cdot a\right) \cdot \left(a \cdot a\right) - 1 \]

   10. Applied rewrites 76.1%

       \[\leadsto \left(a \cdot a\right) \cdot \left(a \cdot a\right) - 1 \]

   if 5.70000000000000004e76 < b

   1. Initial program 60.3%

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

   2. Taylor expanded in b around inf

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

      1. lower-pow.f64 99.9

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

   4. Applied rewrites 99.9%

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

      1. lift-pow.f64 N/A

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

      2. metadata-eval N/A

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

      3. pow-prod-up N/A

         \[\leadsto {b}^{2} \cdot \color{blue}{{b}^{2}} \]

      4. lower-*.f64 N/A

         \[\leadsto {b}^{2} \cdot \color{blue}{{b}^{2}} \]

      5. pow2 N/A

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

      6. lift-*.f64 N/A

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

      7. pow2 N/A

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

      8. lift-*.f64 99.9

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

   6. Applied rewrites 99.9%

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

Alternative 7: 66.6% accurate, 7.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq 900000000000:\\ \;\;\;\;\left(a \cdot a\right) \cdot 4 - 1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot b\right) \cdot \left(b \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (a b)
 :precision binary64
 (if (<= b 900000000000.0) (- (* (* a a) 4.0) 1.0) (* (* b b) (* b b))))

C

double code(double a, double b) {
	double tmp;
	if (b <= 900000000000.0) {
		tmp = ((a * a) * 4.0) - 1.0;
	} else {
		tmp = (b * b) * (b * b);
	}
	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 <= 900000000000.0d0) then
        tmp = ((a * a) * 4.0d0) - 1.0d0
    else
        tmp = (b * b) * (b * b)
    end if
    code = tmp
end function

Java

public static double code(double a, double b) {
	double tmp;
	if (b <= 900000000000.0) {
		tmp = ((a * a) * 4.0) - 1.0;
	} else {
		tmp = (b * b) * (b * b);
	}
	return tmp;
}

Python

def code(a, b):
	tmp = 0
	if b <= 900000000000.0:
		tmp = ((a * a) * 4.0) - 1.0
	else:
		tmp = (b * b) * (b * b)
	return tmp

Julia

function code(a, b)
	tmp = 0.0
	if (b <= 900000000000.0)
		tmp = Float64(Float64(Float64(a * a) * 4.0) - 1.0);
	else
		tmp = Float64(Float64(b * b) * Float64(b * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(a, b)
	tmp = 0.0;
	if (b <= 900000000000.0)
		tmp = ((a * a) * 4.0) - 1.0;
	else
		tmp = (b * b) * (b * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[a_, b_] := If[LessEqual[b, 900000000000.0], N[(N[(N[(a * a), $MachinePrecision] * 4.0), $MachinePrecision] - 1.0), $MachinePrecision], N[(N[(b * b), $MachinePrecision] * N[(b * b), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if b < 9e11

   1. Initial program 77.0%

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

   2. Taylor expanded in a around -inf

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

      1. *-commutative N/A

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

      2. lower-*.f64 N/A

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

   4. Applied rewrites 68.0%

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

   5. Taylor expanded in a around 0

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

      1. lower-*.f64 N/A

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

      2. pow2 N/A

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

      3. lift-*.f64 N/A

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

      4. *-commutative N/A

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

      5. pow2 N/A

         \[\leadsto \left(a \cdot a\right) \cdot \left(4 + \left(b \cdot b\right) \cdot 2\right) - 1 \]

      6. +-commutative N/A

         \[\leadsto \left(a \cdot a\right) \cdot \left(\left(b \cdot b\right) \cdot 2 + 4\right) - 1 \]

      7. lift-fma.f64 N/A

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

      8. lift-*.f64 68.9

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

   7. Applied rewrites 68.9%

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

   8. Taylor expanded in b around 0

      \[\leadsto \left(a \cdot a\right) \cdot 4 - 1 \]
   9. Step-by-step derivation

   10. Applied rewrites 59.3%

       \[\leadsto \left(a \cdot a\right) \cdot 4 - 1 \]

   if 9e11 < b

   1. Initial program 63.9%

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

   2. Taylor expanded in b around inf

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

      1. lower-pow.f64 90.3

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

   4. Applied rewrites 90.3%

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

      1. lift-pow.f64 N/A

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

      2. metadata-eval N/A

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

      3. pow-prod-up N/A

         \[\leadsto {b}^{2} \cdot \color{blue}{{b}^{2}} \]

      4. lower-*.f64 N/A

         \[\leadsto {b}^{2} \cdot \color{blue}{{b}^{2}} \]

      5. pow2 N/A

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

      6. lift-*.f64 N/A

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

      7. pow2 N/A

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

      8. lift-*.f64 90.2

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

   6. Applied rewrites 90.2%

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

Alternative 8: 51.5% accurate, 11.4× speedup

Math

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

FPCore

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

C

double code(double a, double b) {
	return ((a * a) * 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 = ((a * a) * 4.0d0) - 1.0d0
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

1. Initial program 73.9%

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

2. Taylor expanded in a around -inf

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

   1. *-commutative N/A

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

   2. lower-*.f64 N/A

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

4. Applied rewrites 65.3%

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

5. Taylor expanded in a around 0

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

   1. lower-*.f64 N/A

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

   2. pow2 N/A

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

   3. lift-*.f64 N/A

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

   4. *-commutative N/A

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

   5. pow2 N/A

      \[\leadsto \left(a \cdot a\right) \cdot \left(4 + \left(b \cdot b\right) \cdot 2\right) - 1 \]

   6. +-commutative N/A

      \[\leadsto \left(a \cdot a\right) \cdot \left(\left(b \cdot b\right) \cdot 2 + 4\right) - 1 \]

   7. lift-fma.f64 N/A

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

   8. lift-*.f64 66.7

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

7. Applied rewrites 66.7%

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

8. Taylor expanded in b around 0

   \[\leadsto \left(a \cdot a\right) \cdot 4 - 1 \]
9. Step-by-step derivation

10. Applied rewrites 51.5%

    \[\leadsto \left(a \cdot a\right) \cdot 4 - 1 \]
11. Add Preprocessing

Alternative 9: 27.8% accurate, 14.5× speedup

Math

\[\begin{array}{l} \\ 4 \cdot \left(a \cdot a\right) \end{array} \]

FPCore

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

C

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

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 = 4.0d0 * (a * a)
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

code[a_, b_] := N[(4.0 * N[(a * a), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 73.9%

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

2. Taylor expanded in a around -inf

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

   1. *-commutative N/A

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

   2. lower-*.f64 N/A

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

4. Applied rewrites 53.0%

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

5. Taylor expanded in a around 0

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

   1. *-commutative N/A

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

   2. lower-*.f64 N/A

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

   3. +-commutative N/A

      \[\leadsto \left(\left(2 \cdot {b}^{2} + a \cdot \left(4 + a\right)\right) + 4\right) \cdot {a}^{2} \]

   4. lower-+.f64 N/A

      \[\leadsto \left(\left(2 \cdot {b}^{2} + a \cdot \left(4 + a\right)\right) + 4\right) \cdot {a}^{2} \]

   5. +-commutative N/A

      \[\leadsto \left(\left(a \cdot \left(4 + a\right) + 2 \cdot {b}^{2}\right) + 4\right) \cdot {a}^{2} \]

   6. *-commutative N/A

      \[\leadsto \left(\left(\left(4 + a\right) \cdot a + 2 \cdot {b}^{2}\right) + 4\right) \cdot {a}^{2} \]

   7. lower-fma.f64 N/A

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, 2 \cdot {b}^{2}\right) + 4\right) \cdot {a}^{2} \]

   8. lower-+.f64 N/A

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, 2 \cdot {b}^{2}\right) + 4\right) \cdot {a}^{2} \]

   9. *-commutative N/A

      \[\leadsto \left(\mathsf{fma}\left(4 + a, a, {b}^{2} \cdot 2\right) + 4\right) \cdot {a}^{2} \]

   10. lower-*.f64 N/A

       \[\leadsto \left(\mathsf{fma}\left(4 + a, a, {b}^{2} \cdot 2\right) + 4\right) \cdot {a}^{2} \]

   11. pow2 N/A

       \[\leadsto \left(\mathsf{fma}\left(4 + a, a, \left(b \cdot b\right) \cdot 2\right) + 4\right) \cdot {a}^{2} \]

   12. lift-*.f64 N/A

       \[\leadsto \left(\mathsf{fma}\left(4 + a, a, \left(b \cdot b\right) \cdot 2\right) + 4\right) \cdot {a}^{2} \]

   13. pow2 N/A

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

   14. lift-*.f64 55.6

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

7. Applied rewrites 55.6%

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

8. Taylor expanded in b around 0

   \[\leadsto \left(4 + a \cdot \left(4 + a\right)\right) \cdot \left(a \cdot a\right) \]
9. Step-by-step derivation

   1. +-commutative N/A

      \[\leadsto \left(a \cdot \left(4 + a\right) + 4\right) \cdot \left(a \cdot a\right) \]

   2. *-commutative N/A

      \[\leadsto \left(\left(4 + a\right) \cdot a + 4\right) \cdot \left(a \cdot a\right) \]

   3. lower-fma.f64 N/A

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

   4. lift-+.f64 46.0

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

10. Applied rewrites 46.0%

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

11. Taylor expanded in a around 0

    \[\leadsto 4 \cdot \left(a \cdot a\right) \]
12. Step-by-step derivation

13. Applied rewrites 27.8%

    \[\leadsto 4 \cdot \left(a \cdot a\right) \]
14. Add Preprocessing

Reproduce

herbie shell --seed 2025092 
(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))