update documentation

Co-authored-by: Marcel Koch <marcel.koch@kit.edu>

examples/CMakeLists.txt

@@ -54,7 +54,7 @@ if(GINKGO_HAVE_PAPI_SDE)
 endif()
 
 if(GINKGO_BUILD_MPI)
-    list(APPEND EXAMPLES_LIST distributed-solver distributed-multigrid-preconditioned-solver-customized)
+    list(APPEND EXAMPLES_LIST distributed-solver distributed-multigrid-preconditioned-solver)
 endif()
 
 find_package(Kokkos 4.1.00 QUIET)

examples/distributed-multigrid-preconditioned-solver-customized/CMakeLists.txt → examples/distributed-multigrid-preconditioned-solver/CMakeLists.txt

@@ -1,10 +1,10 @@
 cmake_minimum_required(VERSION 3.16)
-project(distributed-multigrid-preconditioned-solver-customized)
+project(distributed-multigrid-preconditioned-solver)
 
 # We only need to find Ginkgo if we build this example stand-alone
 if (NOT GINKGO_BUILD_EXAMPLES)
     find_package(Ginkgo 1.10.0 REQUIRED)
 endif()
 
-add_executable(distributed-multigrid-preconditioned-solver-customized distributed-multigrid-preconditioned-solver-customized.cpp)
-target_link_libraries(distributed-multigrid-preconditioned-solver-customized Ginkgo::ginkgo)
+add_executable(distributed-multigrid-preconditioned-solver distributed-multigrid-preconditioned-solver.cpp)
+target_link_libraries(distributed-multigrid-preconditioned-solver Ginkgo::ginkgo)

examples/distributed-multigrid-preconditioned-solver-customized/distributed-multigrid-preconditioned-solver-customized.cpp → examples/distributed-multigrid-preconditioned-solver/distributed-multigrid-preconditioned-solver.cpp

@@ -50,9 +50,16 @@ int main(int argc, char* argv[])
     // non-distributed program. Please note that not all solvers support
     // distributed systems at the moment.
     using solver = gko::solver::Cg<ValueType>;
+    // We use the Schwarz preconditioner to extend non-distributed
+    // preconditioners, like our Jacobi,
+    // to the distributed case. The Schwarz preconditioner wraps another
+    // preconditioner, and applies it only to the local part of a distributed
+    // matrix. This will be used as our distributed multigrid smoother.
     using schwarz = gko::experimental::distributed::preconditioner::Schwarz<
         ValueType, LocalIndexType, GlobalIndexType>;
     using bj = gko::preconditioner::Jacobi<ValueType, LocalIndexType>;
+    // Multigrid and Pgm can accept the distributed matrix, so we still use the
+    // same type as the non-distributed case.
     using mg = gko::solver::Multigrid;
     using pgm = gko::multigrid::Pgm<ValueType, LocalIndexType>;
 
@@ -200,7 +207,8 @@ int main(int argc, char* argv[])
         solver::build()
             .with_criteria(gko::stop::Iteration::build().with_max_iters(4u))
             .on(exec));
-    // It uses Schwarz Jacobi as smoother and GMRES as coarse solver
+    // The multigrid preconditioner uses the Schwarz Jacobi as smoother and Cg
+    // as coarse solver
     auto mg_factory = gko::share(
         mg::build()
             .with_mg_level(pgm::build().with_deterministic(true))

examples/distributed-multigrid-preconditioned-solver-customized/doc/intro.dox → examples/distributed-multigrid-preconditioned-solver/doc/intro.dox

@@ -2,7 +2,7 @@
 <h1>Introduction</h1>
 This distributed multigrid preconditioned solver example should help you understand customizing Ginkgo multigrid in a distributed setting.
 The example will solve a simple 1D Laplace equation where the system can be distributed row-wise to multiple processes.
-Note. Because the stencil is configured equal weighted, the coarsening method does not perform well on this kind of problem.
+Note. Because the stencil for the discretized Laplacian is configured with equal weight, the coarsening method does not perform well on this kind of problem.
 To run the solver with multiple processes, use `mpirun -n NUM_PROCS ./distributed-solver [executor] [num_grid_points] [num_iterations]`.
 
 If you are using GPU devices, please make sure that you run this example with at most as many processes as you have GPU

examples/distributed-multigrid-preconditioned-solver-customized/doc/results.dox → examples/distributed-multigrid-preconditioned-solver/doc/results.dox

@@ -1,5 +1,5 @@
 <h1>Results</h1>
-This is the expected output for `mpirun -n 4 ./distributed-multigrid-preconditioned-solver-customized`:
+This is the expected output for `mpirun -n 4 ./distributed-multigrid-preconditioned-solver`:
 
 @code{.cpp}