Spring 2012
This free short course will meet for 9 hours total (over 3 sessions). It will be offered in spring break, Monday March 5, 1:30-4:30 PM, Tuesday March 6, 1:30-4:30 PM, and Wednesday, 1:30-4:30.
The 3 session short course will be held in the ITTC lab 1-B in the D.H. Hill
main NCSU library. It's a rather tortuous path from the front desk to the lab,
but you can ask at the front desk.
If you e-mail me (Gary Howell, gary_howell@ncsu.edu) in advance I can be sure to have enough course materials on hand.
Class notes can be downloaded
at Intro to
MPI. Sample codes can be downloaded from
sample.tar.gz. See also
Scientific Computing.
Graduate students, postdocs, faculty and staff who are likely to use parallel computation
in research projects or theses are particularly invited. Before
class starts, students who do not already have a Blade Center account are
encouraged to have their advisors request them so they can have
a permanent account. Faculty can request accounts for themselves and
for their students online
from
http://www.ncsu.edu/itd/hpc/About/Contact.php
NC State has several thousand processors available for
high performance computing. This short course introduces
the use of the machines, starting with how to log on and
submit jobs. The course introduces the use of MPI
(Message Passing Interface), the standard library for
message passing parallel computation. Calls to MPI
are embedded in Fortran, C, or C++ codes, enabling
many processors to work together to accomplish a
parallel computation. In the last sesssion, OpenMP
computing is introduced. OpenMP calls (also embedded in
Fortran and C codes) are used to parallelize codes to take
advantage of multi-core machines.
Session 1. How to log into the HPC machines and submit jobs.
Why to use parallel computation. Some simple MPI commands
and example programs. The last half of the time will be
spent in getting an example code to run.
A version of
the lab is Lab 1
Session 2. MPI Collective communications. These can be simple
and efficient. Considerations in efficient parallel computation.
Running some more codes.
The lab is Lab 2
Session 3. MPI (message passing interface) allows codes to
scale to use many processors with
distributed memory. The 3rd session will show how
to use OpenMP to speed computations on multi-core computers.
OpenMP parallelization is often fairly straightforward.
OpenMP
OpenMP2
OpenMP3
On the blade center, most blades have two motherboards. RAM is more easily
accesible from one or the other of the motherboards (NUMA .. or Non Uniform
Memory Access). For OpenMP to scale to use both motherboards effectively, some
more advanced tricks are needed. See for example Tutorial from HPC2012 by Georg Hager, Gerhard Wellein, and Jan Treibig, University of Erlangen-Nuremberg, Germany.
Some previous courses
introduce parallel debugging, profiling, and OpenMP (shared memory programming). See
Previous Courses [Previous courses and links to class notes]
