This paper presents a new software framework for solving large and sparse linear systems on current hybrid architectures, from small servers to high-end supercomputers, embedding multi-core CPUs and Nvidia GPUs at the node level. The framework has a modular structure and is composed of three main components, which separate basic functionalities for managing distributed sparse matrices and executing some sparse matrix computations involved in iterative Krylov projection methods, eventually exploiting multi-threading and CUDA-based programming models, from the functionalities for setup and application of different types of one-level and multi-level algebraic preconditioners.

D'Ambra, P., Durastante, F., Filippone, S. (2023). Parallel Sparse Computation Toolkit[Formula presented]. SOFTWARE IMPACTS, 15 [10.1016/j.simpa.2022.100463].

Parallel Sparse Computation Toolkit[Formula presented]

Filippone S.
2023-01-01

Abstract

This paper presents a new software framework for solving large and sparse linear systems on current hybrid architectures, from small servers to high-end supercomputers, embedding multi-core CPUs and Nvidia GPUs at the node level. The framework has a modular structure and is composed of three main components, which separate basic functionalities for managing distributed sparse matrices and executing some sparse matrix computations involved in iterative Krylov projection methods, eventually exploiting multi-threading and CUDA-based programming models, from the functionalities for setup and application of different types of one-level and multi-level algebraic preconditioners.
2023
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI
English
Algebraic preconditioners
GPU
Heterogeneous computing
HPC
Linear solvers
D'Ambra, P., Durastante, F., Filippone, S. (2023). Parallel Sparse Computation Toolkit[Formula presented]. SOFTWARE IMPACTS, 15 [10.1016/j.simpa.2022.100463].
D'Ambra, P; Durastante, F; Filippone, S
Articolo su rivista
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S2665963822001476-main.pdf

accesso aperto

Tipologia: Versione Editoriale (PDF)
Licenza: Creative commons
Dimensione 980.36 kB
Formato Adobe PDF
980.36 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/324724
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact