Abstract. We design and implement a parallel algebraic multigrid method for isotropic graph Laplacian problems on multicore Graphical Processing Units (GPUs). The proposed AMG method is based on the aggregation framework. The setup phase of the algorithm uses a parallel maximal independent set algorithm in forming aggregates and the resulting coarse level hierarchy is then used in a K-cycle iteration solve phase with a `1-Jacobi smoother. Numerical tests of a parallel implementation of the method for graphics processors are presented to demonstrate its effectiveness. 1
Thesis (Ph.D.)--University of Washington, 2014The interests of this thesis are twofold. First, a two...
In this work we focus on the application phase of AMG preconditioners, and in particular on the choi...
Abstract. Fast, robust and efficient multigrid solvers are a key numer-ical tool in the solution of ...
In this paper, we develop a new parallel auxiliary grid algebraic multigrid (AMG) method to leverage...
Abstract. Algebraic multigrid methods for large, sparse linear systems are a necessity in many compu...
We present an efficient, robust and fully GPU-accelerated aggregation-based al-gebraic multigrid pre...
Algebraic multigrid methods offer the hope that multigrid convergence can be achieved (for at least ...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
We present a new aggregation-based algebraic multigrid method for the iterative solution of linear s...
We explore a GPU implementation of a Krylov-accelerated algebraic multigrid (AMG) algorithm with fle...
We consider linear systems whose matrices are Laplacians of undirected graphs. We present a new aggr...
The efficient utilization of parallel computational capabilities of modern hardware architecture is ...
We consider the iterative solution of linear systems whose matrices are Laplacians of undirected gra...
The need to solve linear systems arising from problems posed on extremely large, unstructured grids ...
Solvers for elliptic partial differential equations are needed in a wide area of scientific applicat...
Thesis (Ph.D.)--University of Washington, 2014The interests of this thesis are twofold. First, a two...
In this work we focus on the application phase of AMG preconditioners, and in particular on the choi...
Abstract. Fast, robust and efficient multigrid solvers are a key numer-ical tool in the solution of ...
In this paper, we develop a new parallel auxiliary grid algebraic multigrid (AMG) method to leverage...
Abstract. Algebraic multigrid methods for large, sparse linear systems are a necessity in many compu...
We present an efficient, robust and fully GPU-accelerated aggregation-based al-gebraic multigrid pre...
Algebraic multigrid methods offer the hope that multigrid convergence can be achieved (for at least ...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
We present a new aggregation-based algebraic multigrid method for the iterative solution of linear s...
We explore a GPU implementation of a Krylov-accelerated algebraic multigrid (AMG) algorithm with fle...
We consider linear systems whose matrices are Laplacians of undirected graphs. We present a new aggr...
The efficient utilization of parallel computational capabilities of modern hardware architecture is ...
We consider the iterative solution of linear systems whose matrices are Laplacians of undirected gra...
The need to solve linear systems arising from problems posed on extremely large, unstructured grids ...
Solvers for elliptic partial differential equations are needed in a wide area of scientific applicat...
Thesis (Ph.D.)--University of Washington, 2014The interests of this thesis are twofold. First, a two...
In this work we focus on the application phase of AMG preconditioners, and in particular on the choi...
Abstract. Fast, robust and efficient multigrid solvers are a key numer-ical tool in the solution of ...