The robustness of AGMG has been assessed on a large test suite of discrete second order elliptic PDEs, comprising
AGMG has been compared against several other stateoftheart linear system solvers; see here for technical details.
Next 8 graphics: Total wall clock time to solve the linear system in microseconds per unknown  vs  number of unknowns
Performed on a computing node with Intel XEON L5420 processors at 2.50GHz, 2012.
Pay attention that bot scales are logarithmic.
Finite Difference
Poisson equation in a Lshaped domain (2D)
Poisson equation in a cube (3D)
Poisson equation in a cube (3D)
 Cubic (p3) Finite Element
Convectiondiffusion equation in square (2D)
Poisson equation in a cube (3D)
Convectiondiffusion equation in a cube (3D)

AGMG has also been tested on some truly large scale HPC systems.
Last 4 graphics: Total wall clock time in seconds to solve the linear stemming from the 7point finite difference discretization of the Poisson equation in a cube.
For all weak scaling plots, the xscale (problem size) is logarithmic whereas the yscale (time) is not. Both scales are logarithmic for the strong scaling plot.
Top right figure: 373248 cores represents more than 80% of the whole machine JUQUEEN, which is ranked eighth in the top 500 supercomputer list of November 2013.
Weak scalability results on Intel Farm (CURIE, 2014):
time as a function of the number of unknowns. (fixed problem size per core) Weak scalability results on Cray XE6 (HERMIT, 2014): time as a function of the number of unknowns (for different problem sizes per core) 
Weak scalability results on IBM BG/Q (JUQUEEN, 2014):
time as a function of the number of unknowns. (fixed problem size per core) Strong scalability results on Cray XE6 (HERMIT, 2014): time as a function of the number of cores (fixed problem size: 87.5x10^{6} unknowns). 
We acknowledge PRACE for awarding us access to resources CURIE (Intel farm at CEA, France), JUQUEEN (IBM BG/Q at Juelich, Germany) and HERMIT (Cray XE6 at HLRS, Stuttgart, Germany).