  In CSL-LICS 2014, Accattoli and Dal Lago showed that there is an
implementation of the ordinary (i.e. strong, pure, call-by-name)
$\lambda$-calculus into models like RAM machines which is polynomial in the
number of $\beta$-steps, answering a long-standing question. The key ingredient
was the use of a calculus with useful sharing, a new notion whose complexity
was shown to be polynomial, but whose implementation was not explored. This
paper, meant to be complementary, studies useful sharing in a call-by-value
scenario and from a practical point of view. We introduce the Fireball
Calculus, a natural extension of call-by-value to open terms for which the
problem is as hard as for the ordinary lambda-calculus. We present three
results. First, we adapt the solution of Accattoli and Dal Lago, improving the
meta-theory of useful sharing. Then, we refine the picture by introducing the
GLAMoUr, a simple abstract machine implementing the Fireball Calculus extended
with useful sharing. Its key feature is that usefulness of a step is
tested---surprisingly---in constant time. Third, we provide a further
optimization that leads to an implementation having only a linear overhead with
respect to the number of $\beta$-steps.
