Average Error: 0.0 → 0.0
Time: 2.0s
Precision: binary64
\[\left(x + y\right) \cdot \left(z + 1\right) \]
\[\mathsf{fma}\left(x + y, z, x + y\right) \]
(FPCore (x y z) :precision binary64 (* (+ x y) (+ z 1.0)))
(FPCore (x y z) :precision binary64 (fma (+ x y) z (+ x y)))
double code(double x, double y, double z) {
	return (x + y) * (z + 1.0);
}
double code(double x, double y, double z) {
	return fma((x + y), z, (x + y));
}
function code(x, y, z)
	return Float64(Float64(x + y) * Float64(z + 1.0))
end
function code(x, y, z)
	return fma(Float64(x + y), z, Float64(x + y))
end
code[x_, y_, z_] := N[(N[(x + y), $MachinePrecision] * N[(z + 1.0), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_] := N[(N[(x + y), $MachinePrecision] * z + N[(x + y), $MachinePrecision]), $MachinePrecision]
\left(x + y\right) \cdot \left(z + 1\right)
\mathsf{fma}\left(x + y, z, x + y\right)

Error

Bits error versus x

Bits error versus y

Bits error versus z

Derivation

  1. Initial program 0.0

    \[\left(x + y\right) \cdot \left(z + 1\right) \]
  2. Applied egg-rr0.0

    \[\leadsto \color{blue}{\mathsf{fma}\left(x + y, z, x + y\right)} \]
  3. Final simplification0.0

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

Reproduce

herbie shell --seed 2022151 
(FPCore (x y z)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, G"
  :precision binary64
  (* (+ x y) (+ z 1.0)))