diff --git a/example/SparseGrid/10_heat_conduction_reticulate_porous_ceramics/main.cu b/example/SparseGrid/10_heat_conduction_reticulate_porous_ceramics/main.cu
old mode 100644
new mode 100755
index 96bc781fd46b8c42ce93b6a0a56be8659ca837f3..bbc4c733bd2d31f8c660cf02288c821729f81ea2
--- a/example/SparseGrid/10_heat_conduction_reticulate_porous_ceramics/main.cu
+++ b/example/SparseGrid/10_heat_conduction_reticulate_porous_ceramics/main.cu
@@ -143,7 +143,9 @@ int main(int argc, char* argv[])
Box<dims, float> box({Lx_low, Ly_low, Lz_low}, {Lx_up, Ly_up, Lz_up});
Ghost<dims, long int> ghost(1);
- typedef grid_dist_id<dims, float, props_full> grid_in_type;
+ // Defining the decomposition and the input grid type
+ typedef CartDecomposition<dims,float, CudaMemory, memory_traits_inte, BoxDistribution<dims,float> > Dec;
+ typedef grid_dist_id<dims, float, props_full, Dec> grid_in_type;
grid_in_type g_dist(sz, box, ghost);
std::cout << "Rank " << v_cl.rank() << " starts loading redistancing result..." << std::endl;
@@ -156,16 +158,19 @@ int main(int argc, char* argv[])
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Create sparse grid
std::cout << "Rank " << v_cl.rank() << " starts creating sparse grid." << std::endl;
- typedef CartDecomposition<dims,float, CudaMemory, memory_traits_inte, BoxDistribution<dims,float> > Dec;
+
- typedef sgrid_dist_id_gpu<dims, float, props_sparse> sparse_grid_type;
+ typedef sgrid_dist_id_gpu<dims, float, props_sparse, CudaMemory, Dec> sparse_grid_type;
sparse_grid_type g_sparse(sz, box, ghost);
g_sparse.setPropNames(prop_names_sparse);
const float d_low = 0.0, d_up = Lx_up;
get_diffusion_domain_sparse_grid<PHI_FULL, PHI_PHASE>(g_dist, g_sparse, d_low, d_up);
+
+ // Alternatively: load sparse grid of diffusion domain from HDF5 file
// g_sparse.load(path_to_redistancing_result + "/" + redistancing_filename);
+
std::cout << "Rank " << v_cl.rank() << " finished creating sparse grid." << std::endl;
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -290,20 +295,21 @@ int main(int argc, char* argv[])
// Iterative diffusion
// const size_t iterations = 1e6;
const size_t iterations = 103;
- const size_t number_write_outs = 1;
+ const size_t number_write_outs = 10;
const size_t interval_write = iterations / number_write_outs; // Find interval for writing to reach
size_t iter = 0;
float t = 0;
// Copy from host to GPU for simulation
g_sparse.template hostToDevice<U_N, U_NPLUS1, K_SINK, PHI_PHASE>();
+ g_sparse.template ghost_get<PHI_PHASE, K_SINK>(RUN_ON_DEVICE | SKIP_LABELLING);
t_iterative_diffusion_total.start();
while(iter <= iterations)
{
if (iter % 2 == 0)
{
t_iteration_wct.start();
- g_sparse.template ghost_get<PHI_PHASE, U_N, K_SINK>(RUN_ON_DEVICE);
+ g_sparse.template ghost_get<U_N>(RUN_ON_DEVICE | SKIP_LABELLING);
t_GPU.startGPU();
g_sparse.template conv2_b<
U_N,
@@ -316,16 +322,16 @@ int main(int argc, char* argv[])
t_GPU.stopGPU();
t_iteration_wct.stop();
- // Write out time to text-file
- out_wct_file << t_iteration_wct.getwct() << ",";
- out_GPUtime_file << t_GPU.getwctGPU() << ",";
+ // Write out time to text-file
+ out_wct_file << t_iteration_wct.getwct() << ",";
+ out_GPUtime_file << t_GPU.getwctGPU() << ",";
t_iteration_wct.reset();
}
else
{
t_iteration_wct.start();
- g_sparse.template ghost_get<PHI_PHASE, U_NPLUS1, K_SINK>(RUN_ON_DEVICE);
+ g_sparse.template ghost_get<U_NPLUS1>(RUN_ON_DEVICE | SKIP_LABELLING);
t_GPU.startGPU();
g_sparse.template conv2_b<
U_NPLUS1,
@@ -336,15 +342,15 @@ int main(int argc, char* argv[])
{(long int) sz[x]-1, (long int) sz[y]-1, (long int) sz[z]-1},
func_heatDiffusion_withSink);
t_GPU.stopGPU();
- t_iteration_wct.stop();
+ t_iteration_wct.stop();
- // Write out time to text-file
- out_wct_file << t_iteration_wct.getwct() << ",";
- out_GPUtime_file << t_GPU.getwctGPU() << ",";
+ // Write out time to text-file
+ out_wct_file << t_iteration_wct.getwct() << ",";
+ out_GPUtime_file << t_GPU.getwctGPU() << ",";
t_iteration_wct.reset();
}
-#if 0
+
if (iter % interval_write == 0)
{
@@ -363,7 +369,7 @@ int main(int argc, char* argv[])
monitor_total_concentration<U_NPLUS1>(g_sparse, t, iter, path_output,"total_conc.csv");
}
}
-#endif
+
t += dt;
iter += 1;
}
diff --git a/example/SparseGrid/9_inhomogeneous_diffusion_porous_catalyst_CaCO3/main.cu b/example/SparseGrid/9_inhomogeneous_diffusion_porous_catalyst_CaCO3/main.cu
index c0d1136e580ae228069a7ea7e28d87e49853b2e4..ea9baec08124eb01c64d2490db645f74642682d8 100755
--- a/example/SparseGrid/9_inhomogeneous_diffusion_porous_catalyst_CaCO3/main.cu
+++ b/example/SparseGrid/9_inhomogeneous_diffusion_porous_catalyst_CaCO3/main.cu
@@ -167,7 +167,10 @@ int main(int argc, char* argv[])
size_t sz[dims] = {v_sz.get(x), v_sz.get(y), v_sz.get(z)};
Box<dims, float> box({Lx_low, Ly_low, Lz_low}, {Lx_up, Ly_up, Lz_up});
Ghost<dims, long int> ghost(1);
- typedef grid_dist_id<dims, float, props_full> grid_in_type;
+
+ // Defining the decomposition and the input grid type
+ typedef CartDecomposition<dims,float, CudaMemory, memory_traits_inte, BoxDistribution<dims,float> > Dec;
+ typedef grid_dist_id<dims, float, props_full, Dec> grid_in_type;
grid_in_type g_dist(sz, box, ghost);
g_dist.load(path_to_redistancing_result + "/" + redistancing_filename); // Load SDF
@@ -191,7 +194,6 @@ int main(int argc, char* argv[])
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Create sparse grid
std::cout << "Rank " << v_cl.rank() << " starts creating sparse grid." << std::endl;
- typedef CartDecomposition<dims,float, CudaMemory, memory_traits_inte, BoxDistribution<dims,float> > Dec;
typedef sgrid_dist_id_gpu<dims, float, props_sparse, CudaMemory, Dec> sparse_grid_type;
sparse_grid_type g_sparse(sz, box, ghost);
g_sparse.setPropNames(prop_names_sparse);
@@ -392,13 +394,14 @@ int main(int argc, char* argv[])
// Copy from host to GPU for simulation
g_sparse.template hostToDevice<CONC_N, CONC_NPLUS1, DIFFUSION_COEFFICIENT, PHI_PHASE>();
+ g_sparse.template ghost_get<DIFFUSION_COEFFICIENT, PHI_PHASE>(RUN_ON_DEVICE | SKIP_LABELLING);
t_iterative_diffusion_total.start();
while(iter <= iterations)
{
if (iter % 2 == 0)
{
t_iteration_wct.start();
- g_sparse.template ghost_get<PHI_PHASE, CONC_N, DIFFUSION_COEFFICIENT>(RUN_ON_DEVICE);
+ g_sparse.template ghost_get<CONC_N>(RUN_ON_DEVICE | SKIP_LABELLING);
t_GPU.startGPU();
g_sparse.template conv3_b<
CONC_N,
@@ -420,7 +423,7 @@ int main(int argc, char* argv[])
else
{
t_iteration_wct.start();
- g_sparse.template ghost_get<PHI_PHASE, CONC_NPLUS1, DIFFUSION_COEFFICIENT>(RUN_ON_DEVICE);
+ g_sparse.template ghost_get<CONC_NPLUS1>(RUN_ON_DEVICE | SKIP_LABELLING);
t_GPU.startGPU();
g_sparse.template conv3_b<
CONC_NPLUS1,