-
```
Is there an easy way to implement an efficient parallel sparse triangular
matrix backsubstitution step using cusp/thrust in the library? This would
enable the utilization of more elaborate precond…
-
As discussed, adding and dropping columns from the active-set matrix `S` is especially inefficient. Because `S` is only used through products with vectors, it seems plausible that we could replace the…
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I try to solve inv(L), where L is the lower triangular matrix generated from cholesky factorization of A. The way I do it:
fac = cholesky(A, ordering_method = 'xxx')
L = fac.L()
L1 = fac(L) ## sinc…
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Hello!
I'm working on a project that needs a large sparse linear system solved each iteration of a simulation, this takes about 90% of each iterations time, the matrix is about 10.000x10.000 in siz…
-
```
Is there an easy way to implement an efficient parallel sparse triangular
matrix backsubstitution step using cusp/thrust in the library? This would
enable the utilization of more elaborate precond…
-
```
Is there an easy way to implement an efficient parallel sparse triangular
matrix backsubstitution step using cusp/thrust in the library? This would
enable the utilization of more elaborate precond…
-
This is an option that can potentially have much better performance compared to using the dense cublas-based solver. It should be compared to the cuSparse based solver.
The factorization itself doe…
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Hi Jouni, im trying to run the code using the example.
However, when i made the triangular mesh with Netgen its keep complaining about: "invalid child edges".
So i search for another mesh examples …
-
```
Is there an easy way to implement an efficient parallel sparse triangular
matrix backsubstitution step using cusp/thrust in the library? This would
enable the utilization of more elaborate precond…
-
```
Is there an easy way to implement an efficient parallel sparse triangular
matrix backsubstitution step using cusp/thrust in the library? This would
enable the utilization of more elaborate precond…