Linear solvers unable to converge

[nithinsomu]

I am trying to solve a simple 5 X 5 system using gmres in warp. The solver returns nan with and without conditioner. Please find below the code used for the same.

import warp as wp
wp.init()
import numpy as np
from warp.optim.linear import cg, bicgstab, gmres, preconditioner

np.random.seed(123)
n=5
A = np.eye(n)
b = np.random.randn(n)

x0 = wp.array(np.ones(n), dtype=float)
A0 = wp.array(A, dtype=float)
b0 = wp.array(b, dtype=float)
M0 = preconditioner(A0, 'diag')

end_iter, err, atol = gmres(A=A0, b=b0, x=x0, maxiter=10000)

I am running it on cpu. Please tell me if I am doing something wrong.

Thanks
Nithin

[gdaviet]

Hi @nithinsomu, I can reproduce the issue, this is due to the current implementation not handling properly a case where the residual converges to zero mid-iteration. This will be fixed in the next release; in the meantime, perturbing the left-hand-side slightly should avoid the issue.

[nithinsomu]

Sounds good. Thank you very much.

[Nicolas Capens]

Fixed by 3425476. Thanks Gilles!