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Update solvers.md
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vpuri3 committed Apr 7, 2022
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Expand Up @@ -26,8 +26,8 @@ CPU-based arrays while Krylov.jl is more general and will support accelerators
like CUDA. Krylov.jl works with CPUs and GPUs and tends to be more efficient than other
Krylov-based methods.

Finally, a user can pass a custom function ofr the linear solve using
`LinearSolveFunction()` if existing solvers are not optimal for their application.
Finally, a user can pass a custom function for handling the linear solve using
`LinearSolveFunction()` if existing solvers are not optimally suited for their application.
The interface is detailed [here](#passing-in-a-custom-linear-solver)

## Full List of Methods
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