So it's not a good idea to write large amounts of data as text. It's really, really, slow, it generates unnecessarily large files, and it's a pain to deal with. Large amounts of data should be written as binary, with only summary data for humans written as text. Make the stuff the computer is going to deal with easy for the computer, and only the stuff you're actually going to sit down and read easy for you to deal with (eg, text).
Whether you're going to write as text or binary, you can use MPI-IO to coordinate your output to the file to generate one large file. We have a little tutorial on the topic (using MPI-IO, HDF5, and NetCDF) here. For MPI-IO, the trick is to define a type (here, a subarray) to describe the local layout of data in terms of the global layout of the file, and then write to the file using that as the "view". Each file sees only its own view, and the MPI-IO library coordinates the output so that as long as the views are non-overlapping, everything comes out as one big file.
If we were writing this out in binary, we'd just point MPI_Write to our data and be done with it; since we're using text, we have to convert out data into a string. We define our array the way we normally would have, except instead of it being of MPI_FLOATs, it's of a new type which is charspernum
characters per number.
The code follows:
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <mpi.h>
float **alloc2d(int n, int m) {
float *data = malloc(n*m*sizeof(float));
float **array = malloc(n*sizeof(float *));
for (int i=0; i<n; i++)
array[i] = &(data[i*m]);
return array;
}
int main(int argc, char **argv) {
int ierr, rank, size;
MPI_Offset offset;
MPI_File file;
MPI_Status status;
MPI_Datatype num_as_string;
MPI_Datatype localarray;
const int nrows=10;
const int ncols=10;
float **data;
char *const fmt="%8.3f ";
char *const endfmt="%8.3f
";
int startrow, endrow, locnrows;
const int charspernum=9;
ierr = MPI_Init(&argc, &argv);
ierr|= MPI_Comm_size(MPI_COMM_WORLD, &size);
ierr|= MPI_Comm_rank(MPI_COMM_WORLD, &rank);
locnrows = nrows/size;
startrow = rank * locnrows;
endrow = startrow + locnrows - 1;
if (rank == size-1) {
endrow = nrows - 1;
locnrows = endrow - startrow + 1;
}
/* allocate local data */
data = alloc2d(locnrows, ncols);
/* fill local data */
for (int i=0; i<locnrows; i++)
for (int j=0; j<ncols; j++)
data[i][j] = rank;
/* each number is represented by charspernum chars */
MPI_Type_contiguous(charspernum, MPI_CHAR, &num_as_string);
MPI_Type_commit(&num_as_string);
/* convert our data into txt */
char *data_as_txt = malloc(locnrows*ncols*charspernum*sizeof(char));
int count = 0;
for (int i=0; i<locnrows; i++) {
for (int j=0; j<ncols-1; j++) {
sprintf(&data_as_txt[count*charspernum], fmt, data[i][j]);
count++;
}
sprintf(&data_as_txt[count*charspernum], endfmt, data[i][ncols-1]);
count++;
}
printf("%d: %s
", rank, data_as_txt);
/* create a type describing our piece of the array */
int globalsizes[2] = {nrows, ncols};
int localsizes [2] = {locnrows, ncols};
int starts[2] = {startrow, 0};
int order = MPI_ORDER_C;
MPI_Type_create_subarray(2, globalsizes, localsizes, starts, order, num_as_string, &localarray);
MPI_Type_commit(&localarray);
/* open the file, and set the view */
MPI_File_open(MPI_COMM_WORLD, "all-data.txt",
MPI_MODE_CREATE|MPI_MODE_WRONLY,
MPI_INFO_NULL, &file);
MPI_File_set_view(file, 0, MPI_CHAR, localarray,
"native", MPI_INFO_NULL);
MPI_File_write_all(file, data_as_txt, locnrows*ncols, num_as_string, &status);
MPI_File_close(&file);
MPI_Type_free(&localarray);
MPI_Type_free(&num_as_string);
free(data[0]);
free(data);
MPI_Finalize();
return 0;
}
Running gives:
$ mpicc -o matrixastxt matrixastxt.c -std=c99
$ mpirun -np 4 ./matrixastxt
$ more all-data.txt
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
2.000 2.000 2.000 2.000 2.000 2.000 2.000 2.000 2.000 2.000
2.000 2.000 2.000 2.000 2.000 2.000 2.000 2.000 2.000 2.000
3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000
3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000
3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000
3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000 3.000