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Algebraic multigrid (AMG) is often viewed as a scalable O(n) solver for sparse linear systems. Yet, parallel AMG lacks scalability due to increasingly large costs associated with communication, both in the initial construction of a multigrid hierarchy as well as the iterative solve phase. This work introduces a parallel implementation of AMG to reduce the cost of communication, yielding an increase in scalability. Standard inter-process communication consists of sending data regardless of thearXiv:1904.05838v2 fatcat:artym4ja6jf3nkuykmmatqmlum