inaccuracy of culaDsteqr
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inaccuracy of culaDsteqr
Hello,
my problem is an inaccuracy of eigenvectors computed by culaDsteqr. In the file "eivectors.pdf" is the 660'th eigenvector, computed with three different algorithms (matlab, Numerical Recipies(Press), CULA) plotted. Whereby matlab and the NR delivers the same eigenvector, some components of the CULA eigenvector differ more than one decade! Why?
The file "test.c" was my code, to make data to check CULA's accuracy. "data.txt" contains the diagonals of the input tridiagonal matrix. I use SUSE 11.3, CULA premium R10, GeForce GTX 275 and CUDA 3.2 .
Yours sincerely
Malte Sommer
my problem is an inaccuracy of eigenvectors computed by culaDsteqr. In the file "eivectors.pdf" is the 660'th eigenvector, computed with three different algorithms (matlab, Numerical Recipies(Press), CULA) plotted. Whereby matlab and the NR delivers the same eigenvector, some components of the CULA eigenvector differ more than one decade! Why?
The file "test.c" was my code, to make data to check CULA's accuracy. "data.txt" contains the diagonals of the input tridiagonal matrix. I use SUSE 11.3, CULA premium R10, GeForce GTX 275 and CUDA 3.2 .
Yours sincerely
Malte Sommer
 Attachments

 test.c
 code to test CULA
 (4.44 KiB) Downloaded 304 times

 data.txt
 first row: diagonal
second row: off diagonal  (31.28 KiB) Downloaded 312 times

 eivectors.pdf
 plot of one eigenvector, computed with CULA, matlab and NR
 (12.26 KiB) Downloaded 307 times
 msommer
 Posts: 2
 Joined: Mon Apr 19, 2010 12:30 am
Re: inaccuracy of culaDsteqr
msommer,
I checked your data using the properties of eigenvalues for tridiagonal (T) matrices: T = V * E * V'
Doing this, I calculated a different answer than MATLAB, but an equally (if not more) valid solution. The function culaEig is a MEX wrapper to culaSteqr.
This shows that MATLAB is finding a valid Eigen solution.
This shows the answer produced by CULA is also a valid Eigen solution.
This shows that the answer produced by MATLAB and CULA are different, yet acceptable.
Hope this helps with your accuracy issues! Let me know if you have any other questions.
Kyle
I checked your data using the properties of eigenvalues for tridiagonal (T) matrices: T = V * E * V'
Doing this, I calculated a different answer than MATLAB, but an equally (if not more) valid solution. The function culaEig is a MEX wrapper to culaSteqr.
 Code: Select all
>> Ein = [ ... your data ... ];
>> Din = [ ... your data ... ];
>> T = diag(Din) + diag(Ein,1) + diag(Ein,+1);
>> [Vec,Eig] = eig(T);
>> T_recon = Vec * Eig * Vec';
>> norm(T) / norm(T_recon)
ans =
1.0000
This shows that MATLAB is finding a valid Eigen solution.
 Code: Select all
>> [culaVec,culaEig] = culaEig(T);
>> culaT_recon = culaVec * culaEig * culaVec';
>> norm(T) / norm(culaT_recon);
ans =
1.0000
This shows the answer produced by CULA is also a valid Eigen solution.
 Code: Select all
>> diffVec = culaVec  Vec;
>> norm( diffVec )
ans =
2.0000
>> norm( diffVec )
This shows that the answer produced by MATLAB and CULA are different, yet acceptable.
Hope this helps with your accuracy issues! Let me know if you have any other questions.
Kyle
 kyle
 Administrator
 Posts: 301
 Joined: Fri Jun 12, 2009 7:47 pm
Re: inaccuracy of culaDsteqr
Dear kyle,
thank you, for your immediate reply, but I repeated your computations in matlab with "format long". The norm ratio of matlab was "norm(T) / norm(T_recon)=1.000000000000003" whereby cula's norm was "norm(T) / norm(culaT_recon)= 1.000000000017061". Ok, the differency is small, but in my physical problem, I compute definitely different results for particular eigenvalues. Comparisons with analytic solutions have shown, that the code is stable.
Yours sincerely
Malte Sommer
thank you, for your immediate reply, but I repeated your computations in matlab with "format long". The norm ratio of matlab was "norm(T) / norm(T_recon)=1.000000000000003" whereby cula's norm was "norm(T) / norm(culaT_recon)= 1.000000000017061". Ok, the differency is small, but in my physical problem, I compute definitely different results for particular eigenvalues. Comparisons with analytic solutions have shown, that the code is stable.
Yours sincerely
Malte Sommer
 msommer
 Posts: 2
 Joined: Mon Apr 19, 2010 12:30 am
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