MPI Kmean initialization

Parallel_Algorithm/MPI/Kmean_mpi.c

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+//#include "../shared/timing.h" //for timer seconds()
+#include <stdio.h>
+#include <stdlib.h>
+#include <float.h> //for FLT_MAX
+#include <mpi.h>
+#include "../shared/make_2D_array.h"
+#include "../shared/ncdf_util.h"
+#include "../shared/math_util.h"
+
+/* This is the name of the data file we will read. */
+#define FILE_NAME "../test_data/Blobs_smp20000_fea30_cls8.nc"
+#define TOL 0.0001 
+#define MAX_ITER 100 
+
+int main() {
+
+ /*
+ ======================================================
+ ---------------- Initialization ---------------------
+ ======================================================
+ */
+
+ int rank, size;
+ MPI_Init(NULL,NULL);
+ MPI_Comm_rank(MPI_COMM_WORLD, &rank);
+ MPI_Comm_size(MPI_COMM_WORLD, &size);
+ //printf("hello world from process %d of %d\n", rank, size);
+
+ size_t N_samples_all,N_samples,N_features,N_clusters,N_repeat;
+ //i for samples; j for features; k for clusters (typically)
+ int i,j,k;
+ int k_best,initial_idx;
+ float** X;
+ float** X_all; //only master node holds the full data
+ int** GUESS;
+ float dist,dist_min,dist_sum_old,dist_sum_new,inert_best=FLT_MAX;
+
+ /*
+ ======================================================
+ -- Read data by master node and distribute over processes --
+ ======================================================
+ */
+
+ double iStart1 = MPI_Wtime(); 
+ // let master core read data and broadcast to other cores
+
+ if (rank == 0){
+ // get input data and its size
+ readX(FILE_NAME,&X_all,&GUESS,&N_samples_all,&N_features,&N_clusters,&N_repeat);
+ }
+ else{
+ /*
+ MPI_Scatter needs to access *X_all in all processes
+ For non-root, we need to assign NULL for prevent memory error
+ */
+ float* dummy_for_X_all=NULL;
+ X_all = &dummy_for_X_all;
+ }
+
+ MPI_Bcast(&N_samples_all,1,MPI_INT,0,MPI_COMM_WORLD);
+ MPI_Bcast(&N_features,1,MPI_INT,0,MPI_COMM_WORLD);
+ MPI_Bcast(&N_clusters,1,MPI_INT,0,MPI_COMM_WORLD);
+ MPI_Bcast(&N_repeat,1,MPI_INT,0,MPI_COMM_WORLD);
+ //printf("%d: %d,%d,%d,%d\n",rank,N_samples_all,N_features,N_clusters,N_repeat);
+
+ /*
+ Assume N_sample_all is divisible by size for now!
+ TBD: use MPI_Scatterv to handle arbitrary size
+ */
+
+ //convert to int to prevent error from unsigned/signed
+ N_samples = (int)N_samples_all / size; 
+ // printf("%d, Local samples: %d \n",rank,N_samples);
+
+ if (rank==0){
+ printf("Last element in global array: %d: %f \n",X_all[N_samples_all-1][N_features-1]);
+ }
+
+ X = Make2DFloatArray(N_samples,N_features);
+ MPI_Scatter(*X_all, N_samples*N_features, MPI_FLOAT, *X,
+ N_samples*N_features, MPI_FLOAT, 0, MPI_COMM_WORLD);
+
+ // check scattered results
+ if (rank==size-1){
+ //convert to int to prevent error from unsigned - signed
+ printf("Last element after sacattering %d: %f \n",rank,X[(int)N_samples-1][(int)N_features-1]);
+ }
+
+ double iElaps1 = MPI_Wtime() - iStart1;
+
+ /*
+ ======================================================
+ ------- Continue to initialize variables
+ ======================================================
+ */
+
+ // each data point belongs to which cluster
+ // values range from 0 to N_cluster-1
+ int* labels = (int *)malloc(N_samples*sizeof(int));
+ // int* labels_best = (int *)malloc(N_samples*sizeof(int));
+
+ // The position of each cluster center.
+ // Two arrays are needed as we are calculating the distance to the
+ // old centers and accumulating the new centers in the same iteration.
+ float** old_cluster_centers = Make2DFloatArray(N_clusters,N_features);
+ float** new_cluster_centers = Make2DFloatArray(N_clusters,N_features);
+
+ // how many data points in the cluster
+ // needed by calculating the average position of data points in each cluster
+ int* cluster_sizes = (int *)malloc(N_clusters*sizeof(int)); 
+
+ /*
+ ======================================================
+ ---------------- Kmean stepping ---------------------
+ ======================================================
+ */
+ MPI_Barrier(MPI_COMM_WORLD);
+ if (rank == 0)
+ printf("=====Applying K-mean======\n");
+
+ /*
+ ======================================================
+ ---------------- Finalization ---------------------
+ ======================================================
+ */
+
+ // write data back to NetCDF file
+ // writeY(FILE_NAME,labels_best, inert_best);
+
+
+ /* get the max timing measured among all processes */
+ double iElaps1_max;
+ MPI_Reduce(&iElaps1, &iElaps1_max, 1, MPI_DOUBLE,
+ MPI_MAX, 0, MPI_COMM_WORLD);
+
+ // print summary
+ if (rank == 0){
+ printf("Best inertia: %f \n",inert_best);
+ /*
+ printf("Kmean total time use (ms): %f \n", iElaps2*1000.0);
+ printf("E-step time use (ms): %f \n", iElaps3a*1000.0);
+ printf("M-step-1st-half time use (ms): %f \n", iElaps3b*1000.0);
+ printf("M-step-2nd-half time use (ms): %f \n", iElaps3c*1000.0);
+ */
+ printf("I/O time use (ms): %f \n", iElaps1_max*1000.0);
+ }
+
+ MPI_Finalize();
+
+ return 0;
+}

Parallel_Algorithm/MPI/compile.sh

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+mpicc -o Kmean_mpi.out -O2 -std=c99 -lnetcdf -fopenmp -lpthread ../shared/make_2D_array.c ../shared/ncdf_util.c ../shared/math_util.c Kmean_mpi.c