move comment

Author: DanielDoehring

examples/tree_2d_dgsem/elixir_advection_implicit_sparse_jacobian.jl

@@ -118,13 +118,16 @@ ode_float_jac_sparse = semidiscretize(semi_float, t_span,
                                       jac_prototype = sparse_cache.jac_prototype,
                                       colorvec = sparse_cache.coloring.colorvec)
 
-# Note: We experimented for linear problems with providing the constant, sparse Jacobian directly via
+# Note: We tried for this linear problem providing the constant, sparse Jacobian directly via
 #
 # const jac_sparse = sparse_jacobian(sparse_adtype, sparse_cache, rhs, du_ode, u0_ode)
-# const jac_sparse_func!(J, u, p, t) = jac_sparse
+# function jac_sparse_func!(J, u, p, t)
+#   J = jac_sparse
+# end
 # SciMLBase.ODEFunction(rhs!, jac_prototype=float.(jac_prototype), colorvec=colorvec, jac = jac_sparse_func!)
 #
-# which turned out to be significantly slower than just using the prototype and the coloring vector. 
+# which turned out (for the considered problems) to be significantly slower than 
+# just using the prototype and the coloring vector.
 
 summary_callback = SummaryCallback()
 analysis_callback = AnalysisCallback(semi_float, interval = 10)

src/semidiscretization/semidiscretization.jl

@@ -137,17 +137,6 @@ function semidiscretize(semi::AbstractSemidiscretization, tspan;
         ode = SciMLBase.ODEFunction(rhs!, jac_prototype = float.(jac_prototype),
                                     colorvec = colorvec)
 
-        # Note: We experimented for linear problems with providing the constant, sparse Jacobian directly via
-        #
-        # const jac_sparse = sparse_jacobian(sparse_adtype, sparse_cache, rhs, du_ode, u0_ode)
-        # function jac_sparse_func!(J, u, p, t)
-        #   J = jac_sparse
-        # end
-        # SciMLBase.ODEFunction(rhs!, jac_prototype=float.(jac_prototype), colorvec=colorvec, jac = jac_sparse_func!)
-        #
-        # which turned out (for the considered problems) to be significantly slower than 
-        # just using the prototype and the coloring vector. 
-
         return ODEProblem{iip, specialize}(ode, u0_ode, tspan, semi)
     else
         return ODEProblem{iip, specialize}(rhs!, u0_ode, tspan, semi)