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Most of the community refers to the `conjugate_gradient_normal` method by the name "Conjugate Gradient Least Squares (CGLS)", I think we should perform a rename in order to conform to this standard.
…
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The conjugate gradient descent algorithm in scipy is slow and prevents the calling function from being jitted by numba. Idea is to find a python version of the CG minimiser that can be jitted to give …
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From what I can tell, the code looks like it's using Jacobi or Gauss-Seidel methods for solving the divergence pressure Laplace equation. I presume Jacobi because that's what's in the GPU gems refere…
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```
This is an enhancement rather than an issue.
It would be nice to have several functions operate across multiple gpus
double gpuSumProd(vec, vec): this would compute the dot-product of two vecto…
-
```
This is an enhancement rather than an issue.
It would be nice to have several functions operate across multiple gpus
double gpuSumProd(vec, vec): this would compute the dot-product of two vecto…
-
```
This is an enhancement rather than an issue.
It would be nice to have several functions operate across multiple gpus
double gpuSumProd(vec, vec): this would compute the dot-product of two vecto…
-
Hi,
I saw that you have implemented competitive gradient descent in your dev-branch, thanks for giving it a try @mikkel !
I just wanted to mention that you seem to have a bug that we also found i…
f-t-s updated
4 years ago
-
```
This is an enhancement rather than an issue.
It would be nice to have several functions operate across multiple gpus
double gpuSumProd(vec, vec): this would compute the dot-product of two vecto…
-
```
This is an enhancement rather than an issue.
It would be nice to have several functions operate across multiple gpus
double gpuSumProd(vec, vec): this would compute the dot-product of two vecto…
-
```
This is an enhancement rather than an issue.
It would be nice to have several functions operate across multiple gpus
double gpuSumProd(vec, vec): this would compute the dot-product of two vecto…