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This paper describes a massively parallel algebraic multigrid method based onnon-smoothed aggregation. It is especially suited for solving heterogeneouselliptic problems as it uses a greedy heuristic algorithm for the aggregationthat detects changes in the coefficients and prevents aggregation across them.Using decoupled aggregation on each process with data agglomeration onto fewerprocesses on the coarse level, it weakly scales well in terms of both totaltime to solution and time per iteration to nearly 300,000 cores. Because ofsimple piecewise constant interpolation between the levels, its memoryconsumption is low and allows solving problems with more than 100,000,000,000degrees of freedom.

A Massively Parallel Algebraic Multigrid Preconditioner based on Aggregation for Elliptic Problems with Heterogeneous Coefficients