What kind of growth is $O(0.24\cdot K\cdot 2^w)$ I've calculated the running time of an algorithm I'm interested in to be

$$O(0.24\cdot K\cdot 2^{w})\,,$$

where $K$ and&nbsp;$w$ are both variables.  ($K$&nbsp;is the number of elements in some set, and $w$&nbsp;is the log of the largest element, so both are variables.)

What kind of growth does this function have? I'll say it is exponential, however I don't know what the 0.24 implies.
If $K$ is constant and $w$ is variable then $0.24\times K\times 2^w$ and the function is exponential in $w$, therefore it is $O(2^w)$.

If $K$ is variable and $w$ is constant then $0.24\times K\times 2^w$ is $O(K)$ - linear in $K$.   

If both $K$  and $w$ are variables then $0.24\times K\times 2^w$ is $O(K2^w)$.

If both $K$  and $w$ are constant then $0.24\times K\times 2^w$ is $O(1)$.

The constant $0.24$ is ignored since it becomes irrelevant when we compare the rate of growth of a function. For more details please see Big-O notation.

We also use $O^*(f(n))$ notation, in particular in analysis of parametrized algorithms, which means that the algorithm runs in 
$O(f(n)p(k))$ for some polynomial $p(k)$. So you could also write it is $O^*(2^w)$ in case $w$ is variable.