Iraqi Kurdistan All in the Timing

Recent Advances in Technology
code shown in the second table. We
see that the addition of only three lines
turns the conventional program into an
MPI parallel program. At the start of
the computation a copy of the program
starts execution on each of the processors
we have available. The two first lines are
calls provided by the MPI system and
provide each of the executing programs
with information on the total number of
processors (the variable np) and a unique
number in the range 0 to np identifying
each processor. Let us assume we have a
system where np equals 1,000 and that
the number of rectangles is equal to one
million. The program then works by
numbering the rectangles used in the computation from 1
to 1,000,000, and processor number 0 computes the sum of
the areas for rectangles number 1, 1001, 2001… and so on up
to one million. Processor number 1 does exactly the same,
except it computes the sum of the areas for rectangles number
2, 1002, 2002… and so on. When each processor has finished
computing their sum, a single MPI Reduce call will combine
the sums from each of the 1,000 processors into a final sum.
The speedup for this kind of problem is directly proportional
to the number of processors used. Running the program
in Table 2 using 100 million rectangles on 12 processors
gives a speedup of about 11.25, which is roughly what one
would expect, allowing some time for overhead. However,
MPI_Comm_size(MPI_COMM_WORLD,&np);
MPI_Comm_rank(MPI_COMM_WORLD,&myid);
NASA’s supercomputing resources have enabled them to exceed previous state-of-theart
magnetospheric models. The figure shows a snapshot from a 3D simulation of the
Earth’s magnetosphere. The plasma density shows formation of helical structures in
front of the magnetosphere. The structures lead to turbulence, which in turn amplifies the
adverse effects of space weather on Earth and its technological systems. In this project,
a typical simulation ran for over 400 hours across more than 4,000 cores on NASA’s
Pleiades supercomputer. (Courtesy Homa Karimabadi, University of California, San Diego/
SciberQuest; Burlen Loring, University of California, Berkeley).
n=1000000;
h=1/n;
for (i = myid+1; i