Minor modification on PairedExplicitRK3 to reduce redundant computati…

…on (#2152) * remove the redundant recalculation of c in the objective function * put verbose and max_iter on the same line as c --------- Co-authored-by: Hendrik Ranocha <[email protected]> Co-authored-by: Daniel Doehring <[email protected]>
trixi-framework · Nov 8, 2024 · e1950ac · e1950ac
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diff --git a/ext/TrixiNLsolveExt.jl b/ext/TrixiNLsolveExt.jl
@@ -15,7 +15,7 @@ end
 using StableRNGs: StableRNG, rand
 
 # Use functions that are to be extended and additional symbols that are not exported
-using Trixi: Trixi, compute_c_coeffs, @muladd
+using Trixi: Trixi, @muladd
 
 # By default, Julia/LLVM does not use fused multiply-add operations (FMAs).
 # Since these FMAs can increase the performance of many numerical algorithms,
@@ -29,9 +29,8 @@ using Trixi: Trixi, compute_c_coeffs, @muladd
 function PairedExplicitRK3_butcher_tableau_objective_function!(c_eq, a_unknown,
                                                                num_stages,
                                                                num_stage_evals,
-                                                               monomial_coeffs,
-                                                               cS2)
-    c_ts = compute_c_coeffs(num_stages, cS2) # ts = timestep
+                                                               monomial_coeffs, c)
+    c_ts = c # ts = timestep
     # For explicit methods, a_{1,1} = 0 and a_{2,1} = c_2 (Butcher's condition)
     a_coeff = [0, c_ts[2], a_unknown...]
     # Equality constraint array that ensures that the stability polynomial computed from 
@@ -74,16 +73,15 @@ end
 # For details, see Proposition 3.2, Equation (3.3) from 
 # Hairer, Wanner: Solving Ordinary Differential Equations 2
 function Trixi.solve_a_butcher_coeffs_unknown!(a_unknown, num_stages, monomial_coeffs,
-                                               c_s2, c;
-                                               verbose, max_iter = 100000)
+                                               c; verbose, max_iter = 100000)
 
     # Define the objective_function
     function objective_function!(c_eq, x)
         return PairedExplicitRK3_butcher_tableau_objective_function!(c_eq, x,
                                                                      num_stages,
                                                                      num_stages,
                                                                      monomial_coeffs,
-                                                                     c_s2)
+                                                                     c)
     end
 
     # RealT is determined as the type of the first element in monomial_coeffs to ensure type consistency

diff --git a/src/time_integration/paired_explicit_runge_kutta/methods_PERK3.jl b/src/time_integration/paired_explicit_runge_kutta/methods_PERK3.jl
@@ -55,7 +55,7 @@ function compute_PairedExplicitRK3_butcher_tableau(num_stages, tspan,
         # Butcher array abscissae c to find Butcher matrix A
         # This function is extended in TrixiNLsolveExt.jl
         a_unknown = solve_a_butcher_coeffs_unknown!(a_unknown, num_stages,
-                                                    monomial_coeffs, cS2, c;
+                                                    monomial_coeffs, c;
                                                     verbose)
     end
     # Fill A-matrix in P-ERK style