  We examine sorting algorithms for $n$ elements whose basic operation is
comparing $t$ elements simultaneously (a $t$-comparator). We focus on
algorithms that use only a single round or two rounds -- comparisons performed
in the second round depend on the outcomes of the first round comparators.
  We design deterministic and randomized algorithms. In the deterministic case,
we show an interesting relation to design theory (namely, to 2-Steiner
systems), which yields a single-round optimal algorithm for $n=t^{2^k}$ with
any $k\ge 1$ and a variety of possible values of $t$. For some values of $t$,
however, no algorithm can reach the optimal (information-theoretic) bound on
the number of comparators. For this case (and any other $n$ and $t$), we show
an algorithm that uses at most three times as many comparators as the
theoretical bound.
  We also design a randomized Las-Vegas two-rounds sorting algorithm for any
$n$ and $t$. Our algorithm uses an asymptotically optimal number of
$O(\max(\frac{n^{3/2}}{t^2},\frac{n}{t}))$ comparators, with high probability,
i.e., with probability at least $1-1/n$. The analysis of this algorithm
involves the gradual unveiling of randomness, using a novel technique which we
coin the binary tree of deferred randomness.
