1 citations · 1 across the 3 of their papers we have counts for
5 papers
Mixed-Precision Computing for Scientific Discovery: Formats, Co-Design, and Responsible Approximation
Emmanuel Agullo, Hartwig Anzt, Daniel Bauer +37
Reduced and mixed precision have moved from a niche optimization to a central design axis in scientific computing and engineering, driven by energy constraints, heterogeneous accel…
Scalable s-step Preconditioned Conjugate Gradient with Chebyshev Basis and Gauss-Seidel Gram Solve
Pasqua D'Ambra, Massimo Bernaschi, Mauro G. Carrozzo +1
We present a variant of the s--step Preconditioned Conjugate Gradient (PCG) method that combines a Chebyshev--stabilized Krylov basis with a Forward Gauss--Seidel (FGS) iteration f…
Inexact Gauss Seidel and Coarse Solvers for AMG and s-step CG
Stephen Thomas, Pasqua D'Ambra
Communication-avoiding Krylov methods require solving small dense Gram systems at each outer iteration. We present a low-synchronization approach based on Forward Gauss--Seidel (FG…
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…
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…