Solving ARPACK with INFO = 3: Seek Help Here!

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In summary, the speaker is experiencing issues with using ARPACK to find the eigenvalues of a matrix. The program returns an INFO = 3, indicating that no shifts could be applied during the cycle. According to Remark 4, there is no specific guideline for selecting the values of NCV and NEV, but it is recommended to have NCV at least twice the value of NEV. The speaker has tried adjusting these values but has not been successful in solving the problem. They are seeking help from anyone who has experience with ARPACK.
  • #1
NeoDevin
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I'm using ARPACK to find the eigenvalues of a matrix, it works for some of the problems I need it for, but for others, it returns INFO = 3, which means:

No shifts could be applied during a cycle of the implicitly restarted Arnoldi iteration. One possibility is to increase the size of NCV relative to NEV. See remark 4 below.

Remark 4 says:

At present there is no a-priori analysis to guide the selection of NCV relative to NEV. The only formal requrement is that NCV > NEV. However, it is recommended that NCV .ge. 2*NEV. If many problems of the same type are to be solved, one should experiment with increasing NCV while keeping NEV fixed for a given test problem. This will usually decrease the required number of OP*x operations but it also increases the work and storage required to maintain the orthogonal basis vectors. The optimal "cross-over" with respect to CPU time is problem dependent and must be determined empirically.

I have tried increasing NCV, and playing with the values of both NEV and NCV, but no luck.

Anyone who has worked with ARPACK, and knows how to solve this problem, your help would be greatly appreciated.
 
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  • #2
Anyone? I'm kinda stuck here, I can't move on until I get this working, and no one around here seems to know why it's doing it, or how to fix it.
 
  • #3


Thank you for reaching out for help with your issue in using ARPACK to find eigenvalues. It seems that you have already taken the necessary steps by increasing NCV and experimenting with the values of NEV and NCV. However, as stated in Remark 4, the optimal values for these parameters may vary depending on the specific problem you are trying to solve. It is recommended to continue experimenting with different combinations of NCV and NEV until you find a suitable solution.

Additionally, you may want to consider seeking help from others who have experience using ARPACK. You can reach out to online forums or communities dedicated to numerical computing and seek advice from experts in this field. They may be able to provide insights or suggestions on how to approach and solve your problem.

In conclusion, don't hesitate to seek help when facing difficulties in using ARPACK. With the help of others, you may be able to find a solution and successfully solve your problem. Good luck!
 

FAQ: Solving ARPACK with INFO = 3: Seek Help Here!

What is ARPACK and what does it mean to solve it?

ARPACK stands for "Arnoldi Package" and is a software library used for solving large-scale, sparse eigenvalue problems. Solving ARPACK means finding the eigenvalues and eigenvectors of a given matrix.

What does the INFO = 3 error mean when using ARPACK?

The INFO = 3 error in ARPACK indicates that there is an error in the input parameters or matrix provided. This could be due to incorrect data types, invalid matrix dimensions, or other issues with the input.

How can I resolve the INFO = 3 error when using ARPACK?

To resolve the INFO = 3 error, you should carefully check your input parameters and ensure they are correct. Make sure the matrix is properly formatted and has the correct dimensions. You can also consult the ARPACK documentation or seek help from other users.

Can I use ARPACK to solve non-symmetric eigenvalue problems?

Yes, ARPACK can be used to solve both symmetric and non-symmetric eigenvalue problems. However, the algorithm used for symmetric problems is different from that used for non-symmetric problems, so you may need to specify this in your input parameters.

How do I know if my ARPACK solution is accurate?

ARPACK uses iterative methods to approximate the eigenvalues and eigenvectors of a matrix. The accuracy of the solution depends on the number of iterations performed and the convergence criteria used. You can check the convergence status and the number of iterations in the output of the ARPACK solver. Additionally, you can compare the results to known solutions or use other methods to validate the accuracy of the ARPACK solution.

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