38 citations · 120 across the 12 of their papers we have counts for
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cs.DC2019★ 4 cited
Improving strong scaling of the Conjugate Gradient method for solving large linear systems using global reduction pipelining
Siegfried Cools, Jeffrey Cornelis, Pieter Ghysels +1
This paper presents performance results comparing MPI-based implementations of the popular Conjugate Gradient (CG) method and several of its communication hiding (or 'pipelined') v…
math.NA2019
Numerically Stable Recurrence Relations for the Communication Hiding Pipelined Conjugate Gradient Method
Siegfried Cools, Jeffrey Cornelis, Wim Vanroose
Pipelined Krylov subspace methods (also referred to as communication-hiding methods) have been proposed in the literature as a scalable alternative to classic Krylov subspace algor…