  In this work, we use algebraic methods for studying distance computation and
subgraph detection tasks in the congested clique model. Specifically, we adapt
parallel matrix multiplication implementations to the congested clique,
obtaining an $O(n^{1-2/\omega})$ round matrix multiplication algorithm, where
$\omega < 2.3728639$ is the exponent of matrix multiplication. In conjunction
with known techniques from centralised algorithmics, this gives significant
improvements over previous best upper bounds in the congested clique model. The
highlight results include:
  -- triangle and 4-cycle counting in $O(n^{0.158})$ rounds, improving upon the
$O(n^{1/3})$ triangle detection algorithm of Dolev et al. [DISC 2012],
  -- a $(1 + o(1))$-approximation of all-pairs shortest paths in $O(n^{0.158})$
rounds, improving upon the $\tilde{O} (n^{1/2})$-round $(2 +
o(1))$-approximation algorithm of Nanongkai [STOC 2014], and
  -- computing the girth in $O(n^{0.158})$ rounds, which is the first
non-trivial solution in this model.
  In addition, we present a novel constant-round combinatorial algorithm for
detecting 4-cycles.
