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cs.DC2025
On the energy efficiency of sparse matrix computations on multi-GPU clusters
Massimo Bernaschi, Alessandro Celestini, Pasqua D'Ambra +1
We investigate the energy efficiency of a library designed for parallel computations with sparse matrices. The library leverages high-performance, energy-efficient Graphics Process…
cs.DC2023★ 9 cited
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…