We define the notion of effective stiffness and show that it can used to
build sparsifiers, algorithms that sparsify linear systems arising from
finite-element discretizations of PDEs. In particular, we show that sampling
$O(n\log n)$ elements according to probabilities derived from effective
stiffnesses yields an high quality preconditioner that can be used to solve the
linear system in a small number of iterations.