  Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many
high-performance graph algorithms as well as for some linear solvers, such as
algebraic multigrid. The scaling of existing parallel implementations of SpGEMM
is heavily bound by communication. Even though 3D (or 2.5D) algorithms have
been proposed and theoretically analyzed in the flat MPI model on Erdos-Renyi
matrices, those algorithms had not been implemented in practice and their
complexities had not been analyzed for the general case. In this work, we
present the first ever implementation of the 3D SpGEMM formulation that also
exploits multiple (intra-node and inter-node) levels of parallelism, achieving
significant speedups over the state-of-the-art publicly available codes at all
levels of concurrencies. We extensively evaluate our implementation and
identify bottlenecks that should be subject to further research.
