From 84bb3aab79b24af89fad323f9be87dd429844d82 Mon Sep 17 00:00:00 2001 From: Alexis Montoison <35051714+amontoison@users.noreply.github.com> Date: Wed, 2 Oct 2024 13:13:23 -0500 Subject: [PATCH] Update README.md --- README.md | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 5140f0b..5c4f75e 100644 --- a/README.md +++ b/README.md @@ -14,11 +14,19 @@ [build-cirrus-url]: https://cirrus-ci.com/github/JuliaSmoothOptimizers/KrylovPreconditioners.jl [codecov-img]: https://codecov.io/gh/JuliaSmoothOptimizers/KrylovPreconditioners.jl/branch/main/graph/badge.svg [codecov-url]: https://app.codecov.io/gh/JuliaSmoothOptimizers/KrylovPreconditioners.jl -[downloads-img]: https://shields.io/endpoint?url=https://pkgs.genieframework.com/api/v1/badge/KrylovPreconditioners -[downloads-url]: https://pkgs.genieframework.com?packages=KrylovPreconditioners +[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 ## 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). The best sidekick of [Krylov.jl](https://github.com/JuliaSmoothOptimizers/Krylov.jl) └(^o^ )Ｘ( ^o^)┘ + +Boosting Performance with KrylovPreconditioners.jl + +Voici les corrections : + +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 perform multiple sparse matrix-dense vector products, as well as triangular solves, more efficiently on various GPUs.