From 2e6939faa4bf2cc51f5e582fab99638d7a2500ff Mon Sep 17 00:00:00 2001 From: cyw Date: Mon, 30 Dec 2024 13:28:15 -0500 Subject: [PATCH] update the README file --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 7f20412..5770c6f 100644 --- a/README.md +++ b/README.md @@ -22,7 +22,7 @@ GPU implementation of Clarabel solver for Julia Documentation

-__clarabel-gpu.jl__ is the GPU implementation of the Clarabel solver, which can solve conic problems of the following form: +__CuClarabel.jl__ is the GPU implementation of the Clarabel solver, which can solve conic problems of the following form: $$ \begin{array}{r} @@ -44,7 +44,7 @@ The set $\mathcal{K}$ is a composition of convex cones; we support zero cones (l ## Installation -- __clarabel-gpu.jl__ can be added via the Julia package manager (type `]`): `pkg> dev https://github.com/cvxgrp/clarabel-gpu.git`, (which will overwrite current use of Clarabel solver). +- __CuClarabel.jl__ can be added via the Julia package manager (type `]`): `pkg> dev https://github.com/cvxgrp/CuClarabel.git`, (which will overwrite current use of Clarabel solver). ## Tutorial Modeling a conic optimization problem is the same as in the original [Clarabel solver](https://clarabel.org/stable/), except with the additional parameter `direct_solve_method`. This can be set to `:cudss` or `:cudssmixed`. Here is a portfolio optimization problem modelled via JuMP: