 
  
  
  
  
 
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.