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Hello,
I am not sure about the underlying multi GPU concept of amgX.
The application I have in mind has the following features:
- distributed memory CFD domain decomposition using scotch
- M…
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### 🚀 The feature, motivation and pitch
Currently, the `torch.linalg` (https://pytorch.org/docs/stable/linalg.html) package provides linear algebra functionalities in pytorch. The CUDA backend is s…
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## PETSc supports OpenCL.
According to
```
https://petsc.org/release/install/install/
```
Run configure with $--download-viennacl$; check config/examples/arch-ci-linux-viennacl.py for example…
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Hi!
I'm setting up a benchmark of different linear algebra libraries, and I was wondering how to produce a large matrix? Libraries often have a `fromList` method or similar.
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Statsmodels is using joblib in a few places for parallel processing where it's under our control. Current usage is mainly for bootstrap and it is not used in the models directly.
However, some of the…
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Hello stdlib developers,
I'm opening this issue to summarize and coalesce upcoming efforts to integrate linear algebra operations in stdlib, in particular:
1) Accessible interfaces for common li…
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Your folks' great work has inspired me to think about a sparse vector/array type, that is usually (much) more space efficient than IntMap. I'm thinking of a Word64 of bits for present/missing, togethe…
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In section "3 Installation":
I think it would be good to remove "so" in this sentence: "On Linux you need copies of CBLAS and LAPACK. Since BLAS and LAPACK exists in multiple versions, **so** a lit…
lojic updated
2 years ago
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Consider using alternatives for AMGCL:
* boost LU decomposition
* Lapack (Linear Algebra Package) with boost
* Intel Math Kernel Library
* Eigen
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Currently there is no way to get a reduced density matrix representation of a density matrix, But a method that would calculate partial trace or Einstein summation of a matrix on target qubits could m…