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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…
math.NA2025★ 1 cited
Communication-reduced Conjugate Gradient Variants for GPU-accelerated Clusters
Massimo Bernaschi, Mauro G. Carrozzo, Alessandro Celestini +2
Linear solvers are key components in any software platform for scientific and engineering computing. The solution of large and sparse linear systems lies at the core of physics-dri…