  We describe a semidefinite programming framework for proving upper bounds on
concrete sifting problems, and show that the Large Sieve can be interpreted as
a special case of this framework. With a small tweak, the Larger Sieve also
falls into this framework.
  We compare the semidefinite approach to the linear programming approach
(i.e., the general framework of the combinatorial sieve and the Selberg sieve),
and show that it has a qualitative advantage in a toy case where the primes are
completely independent from each other. No new sieve-theoretic bounds are
proved.
