Storage and Computational Costs.

We have collected the dominant costs of the simple Jacobi-Davidson approach, in terms of storage and floating point operations, in two tables. The costs are given for iteration ${m}$ of the algorithm:

Item	Storage
Search space	$2{m}$ $n$-vectors
Residual	$2$ $n$-vector
Approx. eigenvector	$1$ $n$-vector
Projected system	$.5$ matrix of order ${m}$
Eigenvectors of proj. system	$1$ matrix of order ${m}$
Correction equation	Depends on selected solver

Action	Work
Search basis	${m}+1$ dot products, ${m}$ updates in iteration ${m}$
Projected system	${m}$ dots
Eigensystem projected system	$O({m}^3)$
Residual	$1$ matrix-vector product, $1$ update
	or ${m}$-fold update
Approx. eigenvector	${m}$-fold update
Correction equation	Depends on choice of solver