diff --git a/src/adp/adp.c b/src/adp/adp.c
index d58e6945d428be6c56dffd66cf67d15254df8f04..d1839b7e3c9236cf172b09f081a1fe4b7100b926 100644
--- a/src/adp/adp.c
+++ b/src/adp/adp.c
@@ -727,7 +727,7 @@ void compute_correction(global_context_t* ctx, float_t Z)
}
-clusters_t Heuristic1(global_context_t *ctx, int verbose)
+clusters_t Heuristic1(global_context_t *ctx)
{
/*
* Heurisitc 1, from paper of Errico, Facco, Laio & Rodriguez
@@ -740,15 +740,8 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
struct timespec start_tot, finish_tot;
double elapsed_tot;
- if(verbose)
- {
- printf("H1: Preliminary cluster assignment\n");
- clock_gettime(CLOCK_MONOTONIC, &start_tot);
- }
-
TIME_DEF;
-
lu_dynamic_array_t all_centers, removed_centers, actual_centers, max_rho;
lu_dynamic_array_allocate(&all_centers);
@@ -758,15 +751,6 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
datapoint_info_t** dp_info_ptrs = (datapoint_info_t**)MY_MALLOC(n*sizeof(datapoint_info_t*));
- struct timespec start, finish;
- double elapsed;
-
-
- if(verbose)
- {
- clock_gettime(CLOCK_MONOTONIC, &start);
- }
-
/* proceed */
MPI_Win win_datapoints;
@@ -779,7 +763,6 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
#else
#pragma omp parallel for
#endif
-
for(idx_t i = 0; i < n; ++i)
{
/*
@@ -813,15 +796,6 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
}
}
- if(verbose)
- {
- clock_gettime(CLOCK_MONOTONIC, &finish);
- elapsed = (finish.tv_sec - start.tv_sec);
- elapsed += (finish.tv_nsec - start.tv_nsec) / 1000000000.0;
- printf("\tFinding putative centers: %.3lfs\n",elapsed);
- clock_gettime(CLOCK_MONOTONIC, &start);
- }
-
/*
* optimized version
*
@@ -843,9 +817,6 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
MPI_Win_create(to_remove_mask, n * sizeof(heap_node), 1, MPI_INFO_NULL, ctx -> mpi_communicator, &win_to_remove_mask);
MPI_Win_fence(0, win_to_remove_mask);
-
-
-
/*
* to remove
* and to reimplement it using rma
@@ -963,15 +934,6 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
MPI_Win_free(&win_to_remove_mask);
free(to_remove_mask);
- if(verbose)
- {
- clock_gettime(CLOCK_MONOTONIC, &finish);
- elapsed = (finish.tv_sec - start.tv_sec);
- elapsed += (finish.tv_nsec - start.tv_nsec) / 1000000000.0;
- printf("\tFinding actual centers: %.3lfs\n",elapsed);
- clock_gettime(CLOCK_MONOTONIC, &start);
- }
-
int n_centers = (int)actual_centers.count;
int tot_centers;
MPI_Allreduce(&n_centers, &tot_centers, 1, MPI_INT, MPI_SUM, ctx -> mpi_communicator);
@@ -983,7 +945,6 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
* then re-scatter them around to get unique cluster labels */
center_t* private_centers_buffer = (center_t*)MY_MALLOC(actual_centers.count * sizeof(center_t));
-
center_t* global_centers_buffer = (center_t*)MY_MALLOC(tot_centers * sizeof(center_t));
for(int i = 0; i < actual_centers.count; ++i)
@@ -1119,15 +1080,6 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
MPI_Barrier(ctx -> mpi_communicator);
- if(verbose)
- {
- clock_gettime(CLOCK_MONOTONIC, &finish);
- elapsed = (finish.tv_sec - start.tv_sec);
- elapsed += (finish.tv_nsec - start.tv_nsec) / 1000000000.0;
- printf("\tTentative clustering: %.3lfs\n",elapsed);
- clock_gettime(CLOCK_MONOTONIC, &start);
- }
-
free(dp_info_ptrs);
free(max_rho.data);
free(removed_centers.data);
@@ -1154,27 +1106,10 @@ clusters_t Heuristic1(global_context_t *ctx, int verbose)
c_all.centers = actual_centers;
-
- if(verbose)
- {
- clock_gettime(CLOCK_MONOTONIC, &finish);
- elapsed = (finish.tv_sec - start.tv_sec);
- elapsed += (finish.tv_nsec - start.tv_nsec) / 1000000000.0;
- printf("\tFinalizing clustering: %.3lfs\n",elapsed);
- printf("\n");
- }
-
clock_gettime(CLOCK_MONOTONIC, &finish_tot);
elapsed_tot = (finish_tot.tv_sec - start_tot.tv_sec);
elapsed_tot += (finish_tot.tv_nsec - start_tot.tv_nsec) / 1000000000.0;
-
- if(verbose)
- {
- printf("\tFound %lu clusters\n",(uint64_t)actual_centers.count);
- printf("\tTotal time: %.3lfs\n\n", elapsed_tot);
- }
-
c_all.n = n;
return c_all;
}
@@ -2060,8 +1995,8 @@ void Heuristic3(global_context_t* ctx, clusters_t* cluster, float_t Z, int halo)
//int halo_flag = max_border_den_array[cidx] > dp_info[i].log_rho_c ;
//changed_here
- //dp_info[i].cluster_idx = halo_flag ? -1 : cidx;
- dp_info[i].halo_flag = halo_flag;
+ //halo points have cidx < 0 (old cidx = (c + 1) * -1 )
+ dp_info[i].cluster_idx = halo_flag ? (cidx * (-1)) - 1 : cidx;
}
}
free(max_border_den_array);
diff --git a/src/adp/adp.h b/src/adp/adp.h
index 605833b3da1f729c63d3181a5504d99efb5d0524..4db27b2d8934a761dabecae7ab6973e231146f11 100644
--- a/src/adp/adp.h
+++ b/src/adp/adp.h
@@ -52,7 +52,7 @@ void compute_density_kstarnn_rma_v2(global_context_t* ctx, const float_t d, int
float_t compute_ID_two_NN_ML(global_context_t* ctx, datapoint_info_t* dp_info, idx_t n, int verbose);
void clusters_allocate(clusters_t * c, int s);
-clusters_t Heuristic1(global_context_t *ctx, int verbose);
+clusters_t Heuristic1(global_context_t *ctx);
void Heuristic2(global_context_t* ctx, clusters_t* cluster);
void Heuristic3(global_context_t* ctx, clusters_t* cluster, float_t Z, int halo);
void clusters_free(clusters_t * c);
diff --git a/src/common/common.h b/src/common/common.h
index 04da7290db6dd1f44a6d10830594245fd0ad68fa..4130eef9bd363475401f692043c53b57c234a26f 100644
--- a/src/common/common.h
+++ b/src/common/common.h
@@ -22,16 +22,15 @@
//#define PRINT_ORDERED_BUFFER
typedef struct datapoint_info_t {
- idx_t array_idx;
heap ngbh;
+ int is_center;
+ int cluster_idx;
+ idx_t array_idx;
+ idx_t kstar;
float_t g;
float_t log_rho;
float_t log_rho_c;
float_t log_rho_err;
- idx_t kstar;
- int is_center;
- int cluster_idx;
- int halo_flag;
} datapoint_info_t;
#define MAX(A,B) ((A) > (B) ? (A) : (B))
diff --git a/src/main/main.c b/src/main/main.c
index 54757c62ae22fca808324f4deff8f60b748aa389..71836341577a2232003816593c2501201922ac7a 100644
--- a/src/main/main.c
+++ b/src/main/main.c
@@ -104,6 +104,9 @@ int main(int argc, char** argv) {
void simulate_master_read_and_scatter(int dims, size_t n, global_context_t *ctx)
{
+ /* TODO
+ *
+ */
float_t *data;
TIME_DEF
double elapsed_time;
@@ -117,13 +120,11 @@ void simulate_master_read_and_scatter(int dims, size_t n, global_context_t *ctx)
{
test_file_path(OUT_DATA);
test_file_path(OUT_CLUSTER_ASSIGN);
- if(halo) test_file_path(OUT_HALO_FLAGS);
}
else
{
test_distributed_file_path(ctx, OUT_DATA);
test_distributed_file_path(ctx, OUT_CLUSTER_ASSIGN);
- if(halo) test_distributed_file_path(ctx, OUT_HALO_FLAGS);
}
@@ -145,14 +146,14 @@ void simulate_master_read_and_scatter(int dims, size_t n, global_context_t *ctx)
// data = read_data_file(ctx,"../norm_data/hd_blobs.npy",5,MY_FALSE);
//1B points
- //data = read_data_file(ctx,"../norm_data/eds_box_acc_normalized",5,MY_FALSE);
+ // data = read_data_file(ctx,"../norm_data/eds_box_acc_normalized",5,MY_FALSE);
// 190M points
// std_g2980844_091_0000
- // data = read_data_file(ctx,"../norm_data/std_g2980844_091_0000",5,MY_TRUE);
+ data = read_data_file(ctx,"../norm_data/std_g2980844_091_0000",5,MY_TRUE);
/* 1M points ca.*/
- data = read_data_file(ctx,"../norm_data/std_LR_091_0001",5,MY_TRUE);
+ // data = read_data_file(ctx,"../norm_data/std_LR_091_0001",5,MY_TRUE);
/* BOX */
// data = read_data_file(ctx,"../norm_data/std_Box_256_30_092_0000",MY_TRUE);
@@ -289,7 +290,7 @@ void simulate_master_read_and_scatter(int dims, size_t n, global_context_t *ctx)
dp_info[i].kstar = -1;
dp_info[i].is_center = -1;
dp_info[i].cluster_idx = -1;
- dp_info[i].halo_flag = 0;
+ //dp_info[i].halo_flag = 0;
}
ctx -> local_datapoints = dp_info;
@@ -326,7 +327,7 @@ void simulate_master_read_and_scatter(int dims, size_t n, global_context_t *ctx)
LOG_WRITE("Density estimate", elapsed_time)
TIME_START;
- clusters_t clusters = Heuristic1(ctx, MY_FALSE);
+ clusters_t clusters = Heuristic1(ctx);
elapsed_time = TIME_STOP;
LOG_WRITE("H1", elapsed_time)
@@ -352,14 +353,6 @@ void simulate_master_read_and_scatter(int dims, size_t n, global_context_t *ctx)
big_ordered_buffer_to_file(ctx, cl, sizeof(int), ctx -> local_n_points, OUT_CLUSTER_ASSIGN);
big_ordered_buffer_to_file(ctx, ctx -> local_data, sizeof(double), ctx -> local_n_points * ctx -> dims, OUT_DATA);
- if(halo)
- {
- int* halo_flags = (int*)MY_MALLOC(ctx -> local_n_points * sizeof(int));
- for(int i = 0; i < ctx -> local_n_points; ++i) cl[i] = ctx -> local_datapoints[i].halo_flag;
- big_ordered_buffer_to_file(ctx, halo_flags, sizeof(int), ctx -> local_n_points, OUT_HALO_FLAGS);
- free(halo_flags);
- }
-
free(cl);
}
@@ -368,14 +361,6 @@ void simulate_master_read_and_scatter(int dims, size_t n, global_context_t *ctx)
distributed_buffer_to_file(ctx, cl, sizeof(int), ctx -> local_n_points, OUT_CLUSTER_ASSIGN);
distributed_buffer_to_file(ctx, ctx -> local_data, sizeof(double), ctx -> local_n_points * ctx -> dims, OUT_DATA);
- if(halo)
- {
- int* halo_flags = (int*)MY_MALLOC(ctx -> local_n_points * sizeof(int));
- for(int i = 0; i < ctx -> local_n_points; ++i) cl[i] = ctx -> local_datapoints[i].halo_flag;
- distributed_buffer_to_file(ctx, halo_flags, sizeof(int), ctx -> local_n_points, OUT_HALO_FLAGS);
- free(halo_flags);
- }
-
free(cl);
}