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Add six Krylov processes #618
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Codecov ReportBase: 97.97% // Head: 98.06% // Increases project coverage by
Additional details and impacted files@@ Coverage Diff @@
## main #618 +/- ##
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+ Coverage 97.97% 98.06% +0.08%
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Files 36 37 +1
Lines 6072 6349 +277
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+ Hits 5949 6226 +277
Misses 123 123
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It looks good to me, thanks!
docs/src/processes.md
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### Notations |
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Similar to the other pages in the doc, I think it misses Krylov processes
as a title followed by one sentence explaining what is here.
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This will be of great help. I have the impression that the code is for the complex case, the algorithms are for the real case, and the description is a mixture :-).
docs/src/processes.md
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```math | ||
\begin{align*} | ||
A V_k &= V_k T_k + \beta_{k+1} v_{k+1} e_k^T = V_{k+1} T_{k+1,k}, \\ | ||
B U_k &= U_k S_k + \bar{\gamma}_{k+1} u_{k+1} e_k^T = U_{k+1} S_{k+1,k}, \\ |
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A bit confused here.
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Do you mean that
docs/src/processes.md
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\bar{\gamma}_2 & \bar{\alpha}_2 & \ddots & \\ | ||
& \ddots & \ddots & \bar{\beta}_k \\ | ||
& & \bar{\gamma}_k & \bar{\alpha}_k | ||
\end{bmatrix}, |
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Looks like
docs/src/processes.md
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``` | ||
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!!! note | ||
We also have the relations $T_k = S_k^T$, $\enspace T_{k,k+1} = \begin{bmatrix} T_{k} & \gamma_{k+1} e_k \end{bmatrix} = S_{k+1,k}^T \enspace$ and $\enspace S_{k,k+1} = \begin{bmatrix} S_{k} & \bar{\beta}_{k+1} e_k \end{bmatrix} = T_{k+1,k}^T$. |
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docs/src/processes.md
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## Symmetric Lanczos | ||
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Out of curiosity, does MathJax allow us to typeset algorithms?
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Also, specify that
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Out of curiosity, does MathJax allow us to typeset algorithms?
I will try pseudocode.js.
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With #637, we should be able to run the processes on GPUs. |
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Co-authored-by: Dominique <[email protected]>
Co-authored-by: Dominique <[email protected]>
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https://juliasmoothoptimizers.github.io/Krylov.jl/previews/PR618/processes/