Numeric.Log:$cexpm1 from log-domain-0.10.2.1, B

Average Error: 0.0 → 0.0

Time: 1.6s

Precision: binary64

Cost: 6720

\[ \begin{array}{c}[x, y] = \mathsf{sort}([x, y])\\ \end{array} \]

Math

\[\left(x \cdot y + x\right) + y \]

↓

\[y + \mathsf{fma}\left(x, y, x\right) \]

FPCore

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

↓

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

C

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

↓

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

Julia

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

↓

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

Wolfram

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

↓

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

Derivation

1. Initial program 0.0

   \[\left(x \cdot y + x\right) + y \]

2. Simplified 0.0

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

   [Start] 0.0	\[ \left(x \cdot y + x\right) + y \]
   +-commutative [=>] 0.0	\[ \color{blue}{y + \left(x \cdot y + x\right)} \]
   fma-def [=>] 0.0	\[ y + \color{blue}{\mathsf{fma}\left(x, y, x\right)} \]

3. Final simplification 0.0

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

Alternatives

Alternative 1
Error	0.9
Cost	585

\[\begin{array}{l} \mathbf{if}\;y \leq -1 \lor \neg \left(y \leq 1\right):\\ \;\;\;\;y + y \cdot x\\ \mathbf{else}:\\ \;\;\;\;y + x\\ \end{array} \]

Alternative 2
Error	0.0
Cost	448

\[y + x \cdot \left(y + 1\right) \]

Alternative 3
Error	9.9
Cost	192

\[y + x \]

Reproduce

herbie shell --seed 2023054 
(FPCore (x y)
  :name "Numeric.Log:$cexpm1 from log-domain-0.10.2.1, B"
  :precision binary64
  (+ (+ (* x y) x) y))