Implementing generalized eigensolver
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- Dominant language
- Cuda
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Description
Hello!
I'm trying to implement a generalized eigensolver into AMGX (i.e. A*x=lambda*M*x). For now, I'm hacking it into SingleIteration_EigenSolver (power iteration method). I'm working on my own fork here. I have managed to enable access to both an A & M matrix in the class but any time I try to call a member function of the M matrix (e.g. m_M->currentView()), I get an invalid memory reference. The pointer is not null.
Any tips to help with this implementation would be greatly appreciated.
Thanks!
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with SingleIteration_EigenSolver and the generalized_eigensolver branch mentioned in the issue, then trace how the M matrix is initialized and accessed at m_M->currentView(). Reproduce the invalid memory reference before proposing an implementation path; done would require a working generalized eigensolver and a confirmed resolution of the M-matrix access failure.
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Assessment
- Domain
- distributed-systems
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100