[petsc-users] default orthogonalization in gmres

[Jed Brown]

Karl Rupp <rupp at mcs.anl.gov> writes:

> However, for Gram-Schmidt you can just compute all the 
> necessary scalar products at the same time (VecMDot) and reuse the 
> common data vector. This gives you a speed-up of a factor of almost two.

It's not a factor of 2, it's a factor of k where k is the size of the
subspace.  Classical Gram-Schmidt needs one reduction per iteration
(normalization can be hidden), but modified needs k reductions.
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