Update README.md

README.md

@@ -1,4 +1,4 @@
-# `KrylovPreconditioners.jl`
+# `KrylovPreconditioners.jl`, the best sidekick of [Krylov.jl](/~https://github.com/JuliaSmoothOptimizers/Krylov.jl) └(^o^ )Ｘ( ^o^)┘
 
 | **Documentation** | **CI** | **Coverage** | **Downloads** |
 |:-----------------:|:------:|:------------:|:-------------:|
@@ -17,14 +17,27 @@
 [downloads-img]: https://img.shields.io/badge/dynamic/json?url=http%3A%2F%2Fjuliapkgstats.com%2Fapi%2Fv1%2Fmonthly_downloads%2FKrylovPreconditioners&query=total_requests&suffix=%2Fmonth&label=Downloads
 [downloads-url]: https://juliapkgstats.com/pkg/KrylovPreconditioners
 
-The best sidekick of [Krylov.jl](/~https://github.com/JuliaSmoothOptimizers/Krylov.jl) └(^o^ )Ｘ( ^o^)┘
-
 ## How to Cite
 
-If you use KrylovPreconditioners.jl in your work, please cite using the format given in [`CITATION.cff`](/~https://github.com/JuliaSmoothOptimizers/KrylovPreconditioners.jl/blob/main/CITATION.cff).
+If you use KrylovPreconditioners.jl in your work, please cite it using the format provided in [`CITATION.cff`](/~https://github.com/JuliaSmoothOptimizers/KrylovPreconditioners.jl/blob/main/CITATION.cff).
+
+## How to Install
+
+To get started with `KrylovPreconditioners.jl`, you can install it using Julia's package manager:
+
+```julia
+julia> ]
+pkg> add KrylovPreconditioners
+```
+
+To use the package alongside `Krylov.jl`, simply import both packages:
+
+```julia
+using Krylov, KrylovPreconditioners
+```
 
 ## Content
 
-To further enhance the performance of [Krylov.jl](/~https://github.com/JuliaSmoothOptimizers/Krylov.jl), especially on GPUs, we recommend using `KrylovPreconditioners.jl`.
-This package provides a variety of preconditioning strategies that can significantly improve convergence rates for Krylov solvers, making them even more efficient for large-scale problems.
-It also contains operators to boost the performance of sparse matrix-dense vector products and sparse triangular solves on different GPUs.
+To enhance the performance of [Krylov.jl](/~https://github.com/JuliaSmoothOptimizers/Krylov.jl), especially on GPUs, we recommend `KrylovPreconditioners.jl`.
+This package provides a variety of preconditioning strategies that significantly improve convergence rates for Krylov solvers, making them more efficient for large-scale problems.
+It also contains operators that improve the efficiency of sparse matrix-dense vector products and sparse triangular solves on different GPUs, ensuring better performance on modern hardware.