NVIDIA / NVIDIA/AMGX

AMGX Fails to Converge to the Correct Solution

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Dominant language
Cuda
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Description

Hello everyone,

I'm currently trying to solve a large linear system using AMGX and I'm a bit stuck. My matrix data is in CSR (Compressed Sparse Row) format. I must confess that my knowledge of linear algebra isn't very strong, which might be part of the problem.

I've attempted to use almost all the default configuration files provided by AMGX, but I can't seem to get the correct results. Interestingly, I can solve the system correctly in MATLAB, but it's too slow, which is why I turned to AMGX.

I'm not sure how to tweak the configuration files to get the correct solution in AMGX. Could anyone offer some advice or share experiences that might point me in the right direction? Any suggestions on specific parameters or configurations that could be crucial for improving the solver's accuracy or performance would be greatly appreciated.

Thank you!
matrix_info.zip

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
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Research direction

Begin by inspecting matrix_info.zip and reproducing the CSR system with the AMGX default configuration files, then compare its result with MATLAB. Determine whether the discrepancy is caused by the matrix data, solver configuration, or convergence criteria; done means documenting a reproducible cause and the configuration or input needed for the correct solution.

Written by the indexing model from the issue text.

Assessment

Domain
hpc
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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