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We should add support for the following formats (both reading and writing):
- `spmat` (MATLAB) — 1-based indexing, just a list of (row, column, value) triples. No matrix size. No special assumpti…
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Need to investigate where the bottlenecks in the block LU algorithm is.
Are all the matrices that are constructed actually sparse?
Can the factorization be done outside Python? Right now it invo…
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Hi @fwilliams !
This project looks really cool, and it looks like it has (or will have?) a feature that I've been looking for: zero-copy binding of scipy sparse matrices to eigen's SparseMatrix. [D…
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## Description:
For the JDS matrix class, implement the `assembleStorage` and `disassembleStorage` methods that convert the data stored in the `_buildCoeff` attribute of the base `SparseMatrix` cla…
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Possibly related to JuliaLang/julia#21370:
On 0.5.1:
```julia
julia> A = sprand(10,10,0.2);
julia> @benchmark 3.0*A
BenchmarkTools.Trial:
memory estimate: 672 bytes
allocs estimate: 4…
jebej updated
2 years ago
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Hello,
I would like to suggest to implement an SVD routine for sparse matrices.
Main motivation is recommender system algorithms:
Such algorithms deal with initialization of input matices (which are …
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The following piece of code assembles the two-dimensional discrete Laplacian on an `n x n` grid:
```
using SparseArrays
using LinearAlgebra
function laplacian_2d(n)
Δ = spdiagm(
-1…
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For some it may be easiest to think of this as a graph problem.
`A` large, distributed, sparse matrix with sparse subdomain `SD` keeps the state an application or process. In the graph analogy, if…
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Due to fixing Issue #49 , this can now be done without adding scipy as a package dependency/requirement.
Sparse matrices are useful and are additionally one of the ndarray/matrix types built into the…
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### 🐛 Describe the bug
```
>>> import torch
>>> torch.randn(46000, 46000, device='cuda:3').to_sparse()
Traceback (most recent call last):
File "", line 1, in
RuntimeError: CUDA error: an il…