(Difference between revisions)
 Revision as of 18:03, 28 July 2006 (view source)Derouler (Talk | contribs) (→Reference)← Older edit Revision as of 18:07, 28 July 2006 (view source)Derouler (Talk | contribs) m (→Algorithm: * -> \cdot)Newer edit → Line 29: Line 29: ::      s = r - alpha * v
::      s = r - alpha * v
::      solve (M$\cdot$shat = s )
::      solve (M$\cdot$shat = s )
- ::      t = A * shat; + ::      t = A$\cdot$shat; ::      omega = (t$\cdot$s) / (t$\cdot$t)
::      omega = (t$\cdot$s) / (t$\cdot$t)
::      x = x + alpha * phat + omega * shat
::      x = x + alpha * phat + omega * shat

## Contents

Biconjugate gradient stabilized method could be summarized as follows

### System of equation

For the given system of equation
Ax = b ;
b = source vector
x = solution variable for which we seek the solution
A = coefficient matrix

M = the preconditioning matrix constructed by matrix A

### Algorithm

Allocate temperary vectors p, phat, s, shat, t, v, rtilde
Allocate temerary reals rho_1, rho_2 , alpha, beta, omega

r := b - A$\cdot$x
rtilde = r

for i := 1 step 1 until max_itr do
rho_1 = rtilde$\cdot$r
if i = 1 then p := r else
beta = (rho_1/rho_2) * (alpha/omega)
p = r + beta * (p - omega * v)
end if
solve (M$\cdot$phat = p )
v = A$\cdot$phat
alpha = rho_1 / (rtilde$\cdot$v)
s = r - alpha * v
solve (M$\cdot$shat = s )
t = A$\cdot$shat;
omega = (t$\cdot$s) / (t$\cdot$t)
x = x + alpha * phat + omega * shat
r = s - omega * t
rho_2 = rho_1
end (i-loop)

deallocate all temp memory
return TRUE

### Reference

1. Richard Barret, Michael Berry, Tony F. Chan, James Demmel, June M. Donato, Jack Dongarra, Victor Eijihout, Roldan Pozo, Charles Romine, Henk Van der Vorst, "Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods" | http://www.netlib.org/linalg/html_templates/