AmgX
swMATH ID:  13440 
Software Authors:  Naumov, M.; Arsaev, M.; Castonguay, P.; Cohen, J.; Demouth, J.; Eaton, J.; Layton, S.; Markovskiy, N.; Reguly, I.; Sakharnykh, N.; Sellappan, V.; Strzodka, R. 
Description:  AmgX: a library for GPU accelerated algebraic multigrid and preconditioned iterative methods. The solution of large sparse linear systems arises in many applications, such as computational fluid dynamics and oil reservoir simulation. In realistic cases the matrices are often so large that they require large scale distributed parallel computing to obtain the solution of interest in a reasonable time. In this paper we discuss the design and implementation of the AmgX library, which provides dropin GPU acceleration of distributed algebraic multigrid (AMG) and preconditioned iterative methods. The AmgX library implements both classical and aggregationbased AMG methods with different selector and interpolation strategies, along with a variety of smoothers and preconditioners, including blockJacobi, GaussSeidel, and incompleteLU factorization. The library contains many of the standard and flexible preconditioned Krylov subspace iterative methods, which can be combined with any of the available multigrid methods or simpler preconditioners. The parallelism in the aggregation scheme exploits parallel graph matching techniques, while the smoothers and preconditioners often rely on parallel graph coloring algorithms. The AMG algorithm implemented in the AmgX library achieves \(25 imes\) speedup on a single GPU against a competitive implementation on the CPU. As will be shown in the numerical experiments section, both setup and solve phases scale well across multiple nodes, sustaining this performance advantage. 
Homepage:  https://developer.nvidia.com/amgx 
Keywords:  AMG; aggregation; classical; preconditioned iterative methods; ILU; graph matching; graph coloring; levelscheduling; MPI; CUDA; GPU; CFD; reservoir simulation 
Related Software:  hypre; CUDA; PETSc; BoomerAMG; CUSPARSE; SparseMatrix; GitHub; CUBLAS; AGMG; MLD2P4; SParCLES; 2LEVD2P4; Trilinos; Python; BootCMatch; PARDISO; AmgXWrapper; PSBLAS; Matlab; MueLu 
Cited in:  11 Publications 
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH  Year 

AmgX: a library for GPU accelerated algebraic multigrid and preconditioned iterative methods. Zbl 1325.65065 Naumov, M.; Arsaev, M.; Castonguay, P.; Cohen, J.; Demouth, J.; Eaton, J.; Layton, S.; Markovskiy, N.; Reguly, I.; Sakharnykh, N.; Sellappan, V.; Strzodka, R. 
2015

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Cited by 41 Authors
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Cited in 9 Serials
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