18 citations · 31 across the 8 of their papers we have counts for
8 papers
Parallel matching-based AMG preconditioners for elliptic equations discretized by IgA
Pasqua D'Ambra, Fabio Durastante, Salvatore Filippone
Isogeometric analysis (IgA) offers enhanced approximation capabilities for the discretization of elliptic boundary-value problems, yet it results in large, sparse, and increasingly…
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…
A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures
Serena Curzel, Fabrizio Ferrandi, Leandro Fiorin +15
Given their increasing size and complexity, the need for efficient execution of deep neural networks has become increasingly pressing in the design of heterogeneous High-Performanc…
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…
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…