Identifying the connected components of a graph, apart from being a fundamental problem
with countless applications, is a key primitive for many other algorithms. In this paper, we …

We design a generic method to reduce the task of finding weighted matchings to that of
finding short augmenting paths in unweighted graphs. This method enables us to provide …

We show that a constant number of self-attention layers can efficiently simulate, and be
simulated by, a constant number of communication rounds of Massively Parallel …

The study of approximate matching in the Massively Parallel Computations (MPC) model
has recently seen a burst of breakthroughs. Despite this progress, however, we still have a …

We present the first conditional hardness results for massively parallel algorithms for some
central graph problems including (approximating) maximum matching, vertex cover …

We provide a simple new randomized contraction approach to the global minimum cut
problem for simple undirected graphs. The contractions exploit 2-out edge sampling from …

Massively parallel computation (MPC) algorithms for graph problems have witnessed a
resurgence of interest in recent years. Despite major progress for numerous graph problems …

We consider the problem of designing fundamental graph algorithms on the model of
Massive Parallel Computation (MPC). The input to the problem is an undirected graph G …

We present a deterministic O (log log log n)-round low-space Massively Parallel
Computation (MPC) algorithm for the classical problem of (Δ+ 1)-coloring on n-vertex …

The Massively Parallel Computation (MPC) model is an emerging model that distills core
aspects of distributed and parallel computation, developed as a tool to solve combinatorial …