Where $x \in [1,2]$, find an upper bound on $|1-fl(x*fl(1/x))|$
Where $fl(x)$ rounds a number to the nearest IEEE 64-bit approximate encoded value.
My Work
64-bit IEEE has a 52-bit fraction with an implied leading 1.
With a hypothetical zero-bit fraction, the maximum approximation error would be $2^{-1}$. With a hypothetical $n$ bit fraction, the maximum approximation error would be $2^{-n-1}$. With a 52-bit fraction, the maximum approximation error would be $2^{-53}$.
The maximum error of $|1 - fl(x \cdot fl(1/x))|$ will be when $x$ is at maximum value of $x=2$ and approximation error is maximized so that $fl(x) = x + 2^{-53}$. This gives us a maximum approximation error of:
\begin{align*} &= 2 \cdot (1/2 + 2^{-53}) + 2^{-53} - 1 \\ &= 2 \cdot (1/2 + 2^{-53}) + 2^{-53} - 1 \\ &\approx 3.33 \cdot 10^{-16} \end{align*}
Is this right? Is it close?
Let $x = s\times 2^k$, where $1\leq s<2$. If $s = 1$, then $fl(1/x) = 2^{-k}$ and $|1 - fl(x \times fl(1/x))| = 0$.
Suppose, that $1 < s < 2$. Then $fl(1/x) = 1/x + \frac{d}{2}\times ulp(1/x)$ for some $-1 \leq d \leq 1$. Further, $ulp(1/x) = ulp(2/s\times 2^{-k-1}) = 2^{-k-1-p}$, where $p = 52$ is the precision of IEEE-754 64-bit floating point number (since $1 < 2/s < 2$).
Therefore $\phi \equiv x \times fl(1/x) = 1 + x\times 2^{-k-1-p}\times\frac{d}{2} = 1 + 2^{-p-1}\times\frac{sd}{2}$. Let $\operatorname{next}(x)$, $\operatorname{prev}(x)$ denote respectively next and previous to $x$ representable number. We have $\operatorname{next}(1) = 1+2^{-p}$ and $\operatorname{prev}(1) = 1-2^{-p-1}$.
Since $1-2^{-p-1} < \phi < 1 + 2^{-p-1}$, we have $\operatorname{prev}(1) \leq \phi < \frac{1}{2}(1 + \operatorname{next}(1))$ and $\operatorname{prev}(1) < fl(\phi) \leq 1$, from which we conclude $|1 - fl(\phi)| \leq 1-\operatorname{prev}(1) = 2^{-p-1} = 2^{-53}$.