The Conjugate Gradient method involves one matrix-vector product, three vector updates, and two inner products per iteration. Some slight computational variants exist that have the same structure (see Reid [179]). Variants that cluster the inner products , a favorable property on parallel machines, are discussed in §.

For a discussion of the Conjugate Gradient method on vector and shared
memory computers, see Dongarra, *et
al.* [166][71]. For discussions
of the method for more general parallel architectures
see Demmel, Heath and Van der Vorst [67] and
Ortega [166], and the references therein.

Mon Nov 20 08:52:54 EST 1995