CPU- and GPU-initiated Communication Strategies for Conjugate Gradient Methods on Large GPU Clusters

The Conjugate Gradient (CG) method is a key building block in numerous applications, yet its low computational intensity and sensitivity to communication overhead make it difficult to scale efficiently on multi-GPU systems. In light of recent advances in multi-GPU communication technologies, we revisit CG parallelization for large-scale GPU clusters.