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Mantis - ALGLIB
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| ID: | Category: | Severity: | Reproducibility: | Date Submitted: | Last Update: |
| 599 | Optimization | feature | have not tried | 2014-02-24 22:06 | 2018-01-02 17:22 |
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| Reporter: | nlagerr | Platform: | |||
| Assigned To: | SergeyB | OS: | |||
| Priority: | normal | OS Version: | |||
| Status: | assigned | Product Version: | 3.8.1 | ||
| Product Build: | Resolution: | open | |||
| Projection: | none | ||||
| ETA: | none | Fixed in Version: | |||
| Programming language: | C# | ||||
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| Summary: | 0000599: sactivesets.sasrebuildbasis could be optimized for sparse constraint matrices | ||||
| Description: |
We are using the Alglib QP solver and were experiencing some performance issues. I profiled the application and it turns out most time was spent in the code that reorthogonalizes the constraint matrices. The documentation already points out the algorithm does not scale well in the number of constraints. For our particular QP, the constraint matrices are very sparse. I managed to get significant performance improvements by rewriting sasrebuildbasis to exploit this fact. I implemented a vector that: - Inserts elements in O(1) - Removes elements in O(1) - Computes the dot product in O(nr-non-zeros) This data structure does use more memory than normal matrices to achieve these characteristics. If you are interested in implementing the above functionality and would like to have a reference implementation in C#, please contact me via email. |
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| Issue History | |||||
| Date Modified | Username | Field | Change | ||
| 2014-02-24 22:06 | nlagerr | New Issue | |||
| 2014-02-24 22:06 | nlagerr | Programming language | => C# | ||
| 2014-06-02 17:37 | nlagerr | Note Added: 0000067 | |||
| 2018-01-02 17:22 | SergeyB | Status | new => assigned | ||
| 2018-01-02 17:22 | SergeyB | Assigned To | => SergeyB | ||
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