From 5e095f282a7fbad04c04784127444f691d90a473 Mon Sep 17 00:00:00 2001
From: Sathvik Bhagavan <35105271+sathvikbhagavan@users.noreply.github.com>
Date: Thu, 12 Oct 2023 11:03:43 +0530
Subject: [PATCH] docs: update advanced.md

---
 docs/src/tutorials/advanced.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/src/tutorials/advanced.md b/docs/src/tutorials/advanced.md
index 1982d8855..01a337e12 100644
--- a/docs/src/tutorials/advanced.md
+++ b/docs/src/tutorials/advanced.md
@@ -281,7 +281,7 @@ For more information on the preconditioner interface, see the
 To cut down the of Jacobian building overhead, we can choose to exploit the sparsity pattern and deploy matrix coloring during Jacobian construction. With NonlinearSolve.jl, we can simply use `autodiff=AutoSparseForwardDiff()` to automatically exploit the sparsity pattern of Jacobian matrices:
 
 ```@example ill_conditioned_nlprob
-@benchmark solve(prob_brusselator_2d,
+@btime solve(prob_brusselator_2d,
     NewtonRaphson(linsolve = KrylovJL_GMRES(), precs = incompletelu, concrete_jac = true,
         autodiff = AutoSparseForwardDiff()));
 nothing # hide
@@ -295,7 +295,7 @@ colorvec = ArrayInterface.matrix_colors(jac_sparsity)
 ff = NonlinearFunction(brusselator_2d_loop; jac_prototype = float.(jac_sparsity), colorvec)
 prob_brusselator_2d_sparse = NonlinearProblem(ff, u0, p)
 
-@benchmark solve(prob_brusselator_2d_sparse,
+@btime solve(prob_brusselator_2d_sparse,
     NewtonRaphson(linsolve = KrylovJL_GMRES(), precs = incompletelu, concrete_jac = true,
         autodiff = AutoSparseForwardDiff()));
 nothing # hide