18 citations · 38 across the 8 of their papers we have counts for
10 papers
Optimal Polynomial Smoothers for Parallel AMG
Pasqua D'Ambra, Fabio Durastante, Salvatore Filippone +2
In this paper, we explore polynomial accelerators that are well-suited for parallel computations, specifically as smoothers in Algebraic MultiGrid (AMG) preconditioners. These acce…
PSCToolkit: solving sparse linear systems with a large number of GPUs
Pasqua D'Ambra, Fabio Durastante, Salvatore Filippone
In this chapter, we describe the Parallel Sparse Computation Toolkit (PSCToolkit), a suite of libraries for solving large-scale linear algebra problems in an HPC environment. In pa…
Multi-GPU aggregation-based AMG preconditioner for iterative linear solvers
Massimo Bernaschi, Alessandro Celestini, Pasqua D'Ambra +1
We present and release in open source format a sparse linear solver which efficiently exploits heterogeneous parallel computers. The solver can be easily integrated into scientific…
Alya towards Exascale: Algorithmic Scalability using PSCToolkit
Herbert Owen, Oriol Lehmkuhl, Pasqua D'Ambra +2
In this paper, we describe an upgrade of the Alya code with up-to-date parallel linear solvers capable of achieving reliability, efficiency and scalability in the computation of th…
Why diffusion-based preconditioning of Richards equation works: spectral analysis and computational experiments at very large scale
Daniele Bertaccini, Pasqua D'Ambra, Fabio Durastante +1
We consider here a cell-centered finite difference approximation of the Richards equation in three dimensions, averaging for interface values the hydraulic conductivity , a…
Extending Bootstrap AMG for Clustering of Attributed Graphs
Pasqua D'Ambra, Panayot S. Vassilevski, Luisa Cutillo
In this paper we propose a new approach to detect clusters in undirected graphs with attributed vertices. We incorporate structural and attribute similarities between the vertices…
AMG preconditioners for Linear Solvers towards Extreme Scale
Pasqua D'Ambra, Fabio Durastante, Salvatore Filippone
Linear solvers for large and sparse systems are a key element of scientific applications, and their efficient implementation is necessary to harness the computational power of curr…
Automatic coarsening in Algebraic Multigrid utilizing quality measures for matching-based aggregations
Pasqua D'Ambra, Fabio Durastante, Salvatore Filippone +1
In this paper, we discuss the convergence of an Algebraic MultiGrid (AMG) method for general symmetric positive-definite matrices. The method relies on an aggregation algorithm, na…
Improving Solve Time of aggregation-based adaptive AMG
Pasqua D'Ambra, Panayot S. Vassilevski
This paper proposes improving the solve time of a bootstrap AMG designed previously by the authors. This is achieved by incorporating the information, set of algebraically smooth v…
AMG based on compatible weighted matching for GPUs
Massimo Bernaschi, Pasqua D'Ambra, Dario Pasquini
We describe main issues and design principles of an efficient implementation, tailored to recent generations of Nvidia Graphics Processing Units (GPUs), of an Algebraic Multigrid (…