Update

Author: squarefk

benchmark/cajita/Cajita_ParticleDynamicPartitionerPerformance.cpp

@@ -142,41 +142,7 @@ void performanceTest( std::ostream& stream, MPI_Comm comm,
                 positions[p], Kokkos::pair<int, int>( 0, par_num ),
                 Kokkos::pair<int, int>( 0, 3 ) );
 
-            // try for num_run times
-            for ( int t = 0; t < num_run; ++t )
-            {
-                // ensure every optimization process starts from the same status
-                partitioner.initializePartitionByAverage( comm,
-                                                          global_num_cell );
-
-                // compute local workload
-                local_workload_timer.start( p );
-                auto pws =
-                    Cajita::createParticleDynamicPartitionerWorkloadMeasurer<
-                        partitioner.cell_num_per_tile_dim,
-                        partitioner.num_space_dim, Device>(
-                        pos_view, par_num, global_low_corner,
-                        1.0f / num_cells_per_dim[c], comm );
-                partitioner.setLocalWorkload( &pws );
-                local_workload_timer.stop( p );
-
-                // compute prefix sum matrix
-                prefix_sum_timer.start( p );
-                partitioner.computeFullPrefixSum( comm );
-                prefix_sum_timer.stop( p );
-
-                // optimization
-                bool is_changed = false;
-                // full timer
-                total_optimize_timer.start( p );
-                for ( int i = 0; i < max_optimize_iteration; ++i )
-                {
-                    partitioner.updatePartition( std::rand() % 3, is_changed );
-                    if ( !is_changed )
-                        break;
-                }
-                total_optimize_timer.stop( p );
-            }
+
         }
         // Output results
         outputResults( stream, "insert_tile_num", problem_sizes,