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Lab 1: Getting Started Solution
For this and all future labs, you will be working on the CS Linux Lab system. If you are not physically in a Linux Lab (FAB 88-09 and 88-10), you may remotely log on to it: linuxlab.cs.pdx.edu.
Download and unzip the le lab1.zip from D2L. You'll see a lab1 directory with multiple versions of the sum program:
sum.c sum-pthd.c sum-omp.c sum-mpi.c sum1.chpl sum2.chpl
plus a couple of other les: Makefile, linuxhosts.
Set Up Your Environment
Check which shell you are using (bash, csh, ksh, or other):
linux echo $0
/bin/bash
This info will be useful for setting up environment variables (see below).
Check that you have the latest version of gcc:
linux gcc --version
gcc (Ubuntu 5.4.0-6ubuntu1˜16.04.4) 5.4.0 20160609
Check that you have access to the MPI compiler, mpicc:
linux which mpicc
/usr/bin/mpicc
Use addpkg to add the latest version of Chapel compiler to your environment:
linux addpkg
... (a listing of available packages)
Use arrow keys and the tab key to select chapel-1.16.0; then select <OK and press enter. To e ect the selection, you need to logout your session and re-login.
Compile and Run Pthreads Programs
To compile Pthreads programs, use gcc with -pthread ag:
linux gcc -pthread -g -o sum-pthd sum-pthd.c
The compiled programs are run just like regular C programs:
linux ./sum-pthd
Note that for this sum-pthd.c program, the number of threads is hardwired in the program. In the future, we'll see how to make that adjustable.
Exercise Add a printf statement in the worker() routine to show the id and the work range of each individual thread. You may want to place this statement under a control ag:
#ifdef DEBUG
printf(...);
#endif
This way, the same program can be compiled to two di erent versions:
linux gcc -pthread -g -o sum-pthd sum-pthd.c # regular version
linux gcc -DDEBUG -pthread -g -o sum-pthd-debug sum-pthd.c # debug version
Compile and Run OpenMP Programs
To compile OpenMP programs, use gcc with "-fopenmp" ag:
linux gcc -fopenmp -g -o sum-omp sum-omp.c
Again, the compiled programs are run just like regular C programs:
linux ./sum-omp
Exercises
To see the non-intrusive nature of OpenMP, compile the program without the "-fopenmp" ag, and save it in a di erent target:
linux gcc -g -o sum-omp0 sum-omp.c
The result is an identical copy to the sequential version.
One way to con rm that this target code is di erent from the previous one is to generate and compare their assembly code:
linux gcc -fopenmp -S sum-omp.c
# generate openmp code
linux gcc -S -o sum-omp0.s sum-omp.c
# generate sequential code
linux wc sum-omp.s sum-omp0.s
#
compare
their
sizes
linux diff sum-omp.s sum-omp0.s
#
compare
their
contents
To further con rm that the program sum-omp is indeed running with multiple threads, insert a printf statement inside the for loop to print out the current thread id, which can be obtained by a call to omp get thread num(). For this to work, you also need to include the OpenMP header le:
#include <omp.h
Question: How many threads are being used?
Compile and Run MPI Programs
To compile MPI programs, use the command mpicc (which is a gcc wrapper):
linux mpicc -g -o sum-mpi sum-mpi.c
Before running MPI programs, you need to setup a host le. Copy linuxhosts to your home directory, and set the following environment variable (di erent shells use di erent syntax):
linux export OMPI_MCA_orte_default_hostfile = ˜/linuxhosts # bash, ksh
linux setenv OMPI_MCA_orte_default_hostfile ˜/linuxhosts # csh, tsch
You should include this line in your shell startup le to avoid typing it in every time. For bash, ksh, csh, and tcsh, respectively, the le names are .bash profile, .kshrc, .cshrc, and .tcshrc.
An MPI program is run with the command mpirun, with a ag -n <#copies indicating the number of copies you'd like to execute:
linux mpirun -n 4 ./sum-mpi // running 4 copies of the program
Note that for this program, the number of program copies is speci ed externally at the time of execution.
Exercise Add a printf statement in sum-mpi.c to print out the values of two variables rank (current process id) and size (total number of processes). Compile and run the program to verify that four copies of the code are executed.
Compile and Run Chapel Programs
Unlike the above three cases, where gcc handles all the compilations, to compile Chapel programs, a separate compiler, chpl, is needed:
linux chpl -g -o sum1 sum1.chpl
linux chpl -g -o sum2 sum2.chpl
For running Chapel programs, you need to set the following env variables in your shell startup le:
# for bash, ksh
export GASNET_SPAWNFN=S # note: no space before and after =
export GASNET_SSH_SERVERS="bevatron boson ..." # list of host names
export SSH_CMD=ssh
# for csh, tcsh
setenv GASNET_SPAWNFN S
setenv GASNET_SSH_SERVERS "bevatron boson ..." # list of host names setenv SSH_CMD ssh
The list of host names need to be manually copied from the le linuxhosts.
A Chapel program is run with a ag -nl <#locales indicating the number of locales (i.e. hosts) you'd like to use:
linux ./sum1 -nl 1 // running the program over 1 locale
linux ./sum2 -nl 4 // running the program over 4 locales
Exercises
In both programs, the problem domain size N is a con gurable constant. Try to change it at the time of execution:
linux ./sum1 --N=2000 -nl 1
Chapel view threads as a lower-level concept, hence does not provide a facility to show which thread a speci c code piece in executed by. However, it does provide a facility to show locale information. Add a writeln statement inside the compute() function in sum2.chpl to show where the computation takes place. Use here.id to refer to the current locale's name.
Conclusion
Summarize your experience with these four languages and tools. Which one is your favorite at this point? Remember your answer, and we'll see if you'll change your mind at the end of this course.
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