Information Technology Reference
In-Depth Information
n_p = (my_id<remainder) ? (n-1)/P+1 : (n-1)/P;
i_start_p = 1+my_id
*
((n-1)/P)+min(my_id,remainder);
h = (b-a)/n;
s_p = 0.; x = a+i_start_p
*
h;
for (i=0; i<n_p; i++) {
s_p += f(x); x += h;
}
MPI_Allreduce (&s_p,&sum,1,MPI_DOUBLE,MPI_SUM,MPI_COMM_WORLD);
sum += 0.5
*
(f(a)+f(b));
sum
*
=h;
MPI_Finalize();
return 0;
}
The MPI functions
MPI Comm size
and
MPI Comm rank
give, respectively, the
number of processes
P
and the unique id (between
0
and
P 1
)ofthecurrent
process. The work division, i.e., computation of
n
p
and
i
start
;p
, follows the formulas
(10.8)and(10.9). The
for
-loop implements the formula (10.7) for computing
s
p
.
The
MPI Allreduce
function is a collective reduction operation involving all the
processes. Its effect is that all the local
s
p
values are added up and the final result is
stored in the
sum
variable on all processes. An alternative is to use the
MPI Reduce
function, which runs faster than
MPI Allreduce
, but the final result will only be
available on a chosen process.
Example 10.9.
Let us show below the most important part of an MPI implementa-
tion in C of Algorithm
10.1
.
#include <mpi.h>
#include <malloc.h>
/
*
code omitted for defining functions I,f,D0,N1
*
/
int main (int nargs, char
**
args)
{
int P, my_id, n, n_p, i_start_p, i, k, m, remainder;
int left_neighbor_id, right_neighbor_id;
double dt, dx, alpha, t,
*
u_prev,
*
u;
MPI_Init (&nargs, &args);
MPI_Comm_size(MPI_COMM_WORLD,&P);
MPI_Comm_rank(MPI_COMM_WORLD,&my_id);
/
*
code omitted for choosing n and dt, computing dx,alpha etc.
*
/
remainder = (n-1)%P;
n_p = (my_id<remainder) ? (n-1)/P+1 : (n-1)/P;
i_start_p = my_id
*
((n-1)/P)+min(my_id,remainder);
