Add a preference to disable Polyester

src/Trixi.jl

@@ -80,6 +80,7 @@ using Preferences: @load_preference, set_preferences!
 
 const _PREFERENCE_SQRT = @load_preference("sqrt", "sqrt_Trixi_NaN")
 const _PREFERENCE_LOG = @load_preference("log", "log_Trixi_NaN")
+const _PREFERENCE_POLYESTER = parse(Bool, @load_preference("polyester", "true"))
 
 # finite difference SBP operators
 using SummationByPartsOperators: AbstractDerivativeOperator,

src/auxiliary/auxiliary.jl

@@ -204,36 +204,31 @@ Some discussion can be found at [https://discourse.julialang.org/t/overhead-of-t
 and [https://discourse.julialang.org/t/threads-threads-with-one-thread-how-to-remove-the-overhead/58435](https://discourse.julialang.org/t/threads-threads-with-one-thread-how-to-remove-the-overhead/58435).
 """
 macro threaded(expr)
-    # Use `esc(quote ... end)` for nested macro calls as suggested in
-    # https://github.com/JuliaLang/julia/issues/23221
-    #
-    # The following code is a simple version using only `Threads.@threads` from the
-    # standard library with an additional check whether only a single thread is used
-    # to reduce some overhead (and allocations) for serial execution.
-    #
-    # return esc(quote
-    #   let
-    #     if Threads.nthreads() == 1
-    #       $(expr)
-    #     else
-    #       Threads.@threads $(expr)
-    #     end
-    #   end
-    # end)
-    #
-    # However, the code below using `@batch` from Polyester.jl is more efficient,
-    # since this packages provides threads with less overhead. Since it is written
-    # by Chris Elrod, the author of LoopVectorization.jl, we expect this package
-    # to provide the most efficient and useful implementation of threads (as we use
-    # them) available in Julia.
     # !!! danger "Heisenbug"
     #     Look at the comments for `wrap_array` when considering to change this macro.
-
-    # By using `Trixi.@batch` we allow users of Trixi.jl to use `@threaded` without having
-    # Polyester.jl in their namespace.
-    return esc(quote
-                   Trixi.@batch $(expr)
-               end)
+    expr = if _PREFERENCE_POLYESTER
+        # Currently using `@batch` from Polyester.jl is more efficient, 
+        # bypasses the Julia task scheduler and provides parallelization with less overhead.
+        quote
+            $Trixi.@batch $(expr)
+        end
+    else
+        # The following code is a simple version using only `Threads.@threads` from the
+        # standard library with an additional check whether only a single thread is used
+        # to reduce some overhead (and allocations) for serial execution.
+        quote
+            let
+                if $Threads.nthreads() == 1
+                    $(expr)
+                else
+                    $Threads.@threads :static $(expr)
+                end
+            end
+        end
+    end
+    # Use `esc(quote ... end)` for nested macro calls as suggested in
+    # https://github.com/JuliaLang/julia/issues/23221
+    return esc(expr)
 end
 
 """

src/auxiliary/math.jl

@@ -7,6 +7,21 @@
 
 const TRIXI_UUID = UUID("a7f1ee26-1774-49b1-8366-f1abc58fbfcb")
 
+"""
+    Trixi.set_polyester(toggle::Bool; force = true)
+
+Toggle the usage of [Polyester.jl](https://github.com/JuliaSIMD/Polyester.jl) for multithreading.
+By default, Polyester.jl is enabled, but it can
+be useful for performance comparisons to switch to the Julia core backend.
+
+This does not fully disable Polyester.jl,
+buy only its use as part of Trixi.jl's `@threaded` macro.
+"""
+function set_polyester(toggle::Bool; force = true)
+    set_preferences!(TRIXI_UUID, "polyester" => string(toggle), force = force)
+    @info "Please restart Julia and reload Trixi.jl for the `polyester` change to take effect"
+end
+
 """
     Trixi.set_sqrt_type(type; force = true)
 

src/callbacks_step/summary.jl

@@ -207,6 +207,9 @@ function initialize_summary_callback(cb::DiscreteCallback, u, t, integrator;
 
     # technical details
     setup = Pair{String, Any}["#threads" => Threads.nthreads()]
+    if !_PREFERENCE_POLYESTER
+        push!(setup, "Polyester" => "disabled")
+    end
     if mpi_isparallel()
         push!(setup,
               "#MPI ranks" => mpi_nranks())

src/solvers/dg.jl

@@ -629,7 +629,7 @@ end
     # since LoopVectorization does not support `ForwardDiff.Dual`s. Hence, we use
     # optimized `PtrArray`s whenever possible and fall back to plain `Array`s
     # otherwise.
-    if LoopVectorization.check_args(u_ode)
+    if _PREFERENCE_POLYESTER && LoopVectorization.check_args(u_ode)
         # This version using `PtrArray`s from StrideArrays.jl is very fast and
         # does not result in allocations.
         #