AlgebraicMultigrid.jl

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This is based on https://github.com/julia-actions/julia-invalidations. Adding such checks came up in https://discourse.julialang.org/t/potential-performance-regressions-in-julia-1-8-for-special-un-precompiled-type-dispatches-and-how-to-fix-them/86359. I suggest to add this check here since this package is widely used as a dependency. See also...

ranocha

Extend Ruge-Stuben solver to complex type

2

This PR shows minimum changes to allow `ruge_stuben` to take complex-valued matrix. It seems to converge well for simple problems: ```julia using LinearAlgebra using AlgebraicMultigrid A = poisson((32, 32, 32))...

learning-chip

Reference for direct interpolation used

2

What is the reference for the direct interpolation used in this package? I see that it is an extension to non Z matrices but is there a paper or book...

mohdibntarek

Default ruge_stuben solver diverges for a Poisson problem, due to problematic interpolation

3

## To reproduce Download this [FEMLAB/poisson3Db](https://sparse.tamu.edu/FEMLAB/poisson3Db) file and run: ```julia using MatrixMarket import AlgebraicMultigrid as AMG A = MatrixMarket.mmread("poisson3Db.mtx") b = MatrixMarket.mmread("poisson3Db_b.mtx") |> vec ml = AMG.ruge_stuben(A) x_amg = AMG._solve(ml,...

learning-chip

Support for CuSparse

3

```julia using CUDA, SparseArrays, LinearAlgebra, AlgebraicMultigrid CUDA.allowscalar(false) W = CUDA.CUSPARSE.CuSparseMatrixCSR(sprand(100,100,0.1)) ruge_stuben(W) #= MethodError: no method matching ruge_stuben(::CUDA.CUSPARSE.CuSparseMatrixCSR{Float64, Int32}) Closest candidates are: ruge_stuben(!Matched::Union{Hermitian{Ti, TA}, Symmetric{Ti, TA}, TA}) where {Ti, Tv, TA

ChrisRackauckas

Use sparse LU as a faster coarse solver than Pinv

3

The only available `CoarseSolver` is `Pinv`, which gets very slow if the coarsest-level A is large, for example in a two-grid setting instead of multigrid V-cycle. I wrote a code...

learning-chip

User-defined near null space

5

Hi! First, let me congratulate you for this package, I have been using it and it performs very well! It's faster than PETSc GAMG in many cases according to my...

fverdugo

This NeurIPS 2021 paper seems interesting and relevant. https://openreview.net/pdf?id=xXYjxli-2i

mohdibntarek

Hessian vector products

7

Would it be possible to get some code like below working? The first example with the function `f` is meant to show that this definition of `hessian_vector_product` can work. The...

omalled

Convergence issues

1

[mat.jls.zip](https://github.com/ranjanan/AMG.jl/files/2124648/mat.jls.zip) [vec.jls.zip](https://github.com/ranjanan/AMG.jl/files/2124649/vec.jls.zip) Ref https://github.com/Circuitscape/Circuitscape.jl/issues/129

ranjanan