Discussion Overview
The discussion revolves around encountering an "out of memory" error while attempting to solve a linear optimization problem in MATLAB, specifically using the "fmincon" function with a large-dimension matrix. Participants explore potential solutions and considerations related to memory management in this context.
Discussion Character
- Technical explanation
- Debate/contested
- Mathematical reasoning
Main Points Raised
- One participant suggests using sparse matrix functions to manage memory more effectively.
- Another participant raises the importance of checking for unnecessary copies of matrices or temporary arrays that could contribute to memory issues.
- A participant describes their specific use case involving "fmincon" and the dimensions of the matrices involved, noting that one matrix is in full representation while another is in sparse representation.
- There is a mention that even when attempting to convert the problematic matrix to sparse format, the memory issue persists, possibly due to the minimizer expanding the matrix.
- One participant notes that the size of the matrix structure is not inherently problematic, but the generation of multiple copies during computation could be a contributing factor to the memory error.
- There is a presumption regarding the dimensions of another matrix involved in the optimization process, indicating a concern about its size as well.
Areas of Agreement / Disagreement
Participants express various strategies and considerations regarding memory management, but no consensus is reached on a definitive solution to the memory issue. Multiple competing views and approaches remain present in the discussion.
Contextual Notes
Participants have not fully explored the implications of matrix dimensions and their representations on memory usage. The discussion includes assumptions about the sizes of matrices and the potential for creating multiple copies during optimization processes, but these aspects remain unresolved.