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Line 1: + + + + − <nowiki>#include <stdio.h></nowiki><br>+ − <nowiki>#include <stdlib.h></nowiki><br>+ − <nowiki>#include <time.h></nowiki><br>+ + − int main(int argc, char *argv[])<br>+ − <nowiki>{</nowiki><br>+ − <nowiki>int i,N,incirc=0;</nowiki><br> − <nowiki>double x,y,circrad2;</nowiki><br> − <nowiki>sscanf(argv[1], "%d", &N); // get iteration number from input</nowiki><br>+ − <nowiki>srand(time(NULL)); // seed random number generator</nowiki><br>+ − + − + + + − <nowiki>for(i=0;i<N;i++){</nowiki><br>+ − <nowiki>x=1.0*rand(); y=1.0*rand(); // get rand. point and</nowiki><br>+ − <nowiki>incirc += (x*x+y*y) < circrad2; // check if inside circle</nowiki><br>+ − + − <nowiki>printf("pi=%.12f\n",4.0*incirc/N); // display probability</nowiki><br>+ − return 0;<br>+ − }+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
no edit summary
== C example ==
== C example ==
=== The Problem and the Code ===
=== The Problem and the Code ===
<syntaxhighlight lang="c">
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
int main(int argc, char *argv[])
{
int i,N,incirc=0;
double x,y,circrad2;
sscanf(argv[1], "%d", &N); // get iteration number from input
srand(time(NULL)); // seed random number generator
circrad2=1.0*RAND_MAX;
circrad2*=circrad2; // Define radius squared
<nowiki>circrad2=1.0*RAND_MAX; </nowiki><br>
for(i=0;i<N;i++){
<nowiki>circrad2*=circrad2; // Define radius squared </nowiki><br>
x=1.0*rand(); y=1.0*rand(); // get rand. point and
incirc += (x*x+y*y) < circrad2; // check if inside circle
}
printf("pi=%.12f\n",4.0*incirc/N); // display probability
return 0;
}
} <br>
</syntaxhighlight>
Compiling this program (that we may save as calcpi.c)
<syntaxhighlight lang="bash">
gcc calcpi.c -o calcpi
</syntaxhighlight>
yields an executable calcpi that is ready for submission.
=== Preparation for Job Submission ===
=== Preparation for Job Submission ===
To prepare the job execution space and inform Condor of the appropriate run environment, create a job description file (e.g. calcpi.condor)
<pre>Executable = calcpi<br>
Requirements = ParallelSchedulingGroup == "stats group"<br>
Universe = vanilla<br>
output = calcpi$(Process).out<br>
error = calcpi$(Process).err<br>
Log = calcpi.log<br>
Arguments = 100000000<br>
should_transfer_files = YES<br>
when_to_transfer_output = ON_EXIT<br>
Queue 50</pre>
The last line specifies that 50 instances should be scheduled on the cluster. The description file specifies the executable and the arguments passed to it during execution. (In this case we are requesting that all instances iterate 10e9 times in the program's sampling loop.) The requirement field insists that the job stay on the Statistics Cluster. (All statistics nodes are labeled with "stats group" in their Condor ClassAds) Output and error files are targets for standard out and standard error streams respectively. The log file is used to by Condor to record in real time the progress in job processing. Note that this setup labels output files by process number to prevent a job instance from overwritting files belonging to another. The current values imply that all files are to be found in the same directory as the description file.
The <i>universe</i> variable specifies the condor runtime environment. For the purposes of these independent jobs, the simplest "vanilla" universe suffices. In a more complicated parallel task, with checkpointing and migration, MPI calls etc., more advanced run-time environments are employed, often requiring specilized linking of the binaries. The lines specifying transfer settings are important to avoid any assumptions about accessibility over nfs. They should be included whether or not any output files (aside from standard output and error) are necessary.
=== Job Submission and Management ===
=== Job Submission and Management ===
The job is submitted with:
<syntaxhighlight lang="bash">
condor_submit calcpi.condor
</syntaxhighlight>
The cluster can be queried before or after submission to check its availability. Two very versatile commands exist for this purpose: condor_status and condor_q. The former returns the status of the nodes (broken down by virtual machines that can each handle a job instance.) The latter command shows the job queue including the individual instances of every job and the submission status (e.g. idling, busy etc.) Using condor_q a few seconds after submission shows:
<pre>-- Submitter: stat31.phys.uconn.edu : <192.168.1.41:44831> : stat31.phys.uconn.edu
ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD
33.3 prod 1/30 15:37 0+00:00:02 R 0 9.8 calcpi 100000000
33.4 prod 1/30 15:37 0+00:00:00 R 0 9.8 calcpi 100000000
33.5 prod 1/30 15:37 0+00:00:00 R 0 9.8 calcpi 100000000
33.6 prod 1/30 15:37 0+00:00:00 R 0 9.8 calcpi 100000000
33.7 prod 1/30 15:37 0+00:00:00 R 0 9.8 calcpi 100000000
33.8 prod 1/30 15:37 0+00:00:00 R 0 9.8 calcpi 100000000
6 jobs; 0 idle, 6 running, 0 held</pre>
By this time, only 6 jobs are left on the cluster, all with status 'R' - running. Various statistics are given including a job ID number. This handle is useful if intervention is required like manual removal of frozen job instances from the cluster. Now, comparing the results (e.g. with command cat calcpi*.out) shows
<pre>...
pi=3.141215440000
pi=3.141447360000
pi=3.141418120000
pi=3.141797520000
...</pre>
== R example ==
== R example ==
=== The Problem and the Code ===
=== The Problem and the Code ===