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cluster:103 [2011/12/21 13:51]
hmeij [SAS] |
cluster:103 [2011/12/22 14:34] (current)
hmeij [Submit 2] |
| * SAS/Graphics examples [[http://sas.wesleyan.edu/ricardo2/out/6/10/|Data Driven Images]], [[http://sas.wesleyan.edu/ricardo2/out/6/10/graphics.sas|Code]] | * SAS/Graphics examples [[http://sas.wesleyan.edu/ricardo2/out/6/10/|Data Driven Images]], [[http://sas.wesleyan.edu/ricardo2/out/6/10/graphics.sas|Code]] |
| |
| * A tutor is available at [[http://sas.wesleyan.edu/SASOnlineTutor/sot91/index.htm|http://sas.wesleyan.edu/SASOnlineTutor/sot91/index.htm]] | A tutor application is available at [[http://sas.wesleyan.edu/SASOnlineTutor/sot91/index.htm|http://sas.wesleyan.edu/SASOnlineTutor/sot91/index.htm]] |
| |
| ==== Program ==== | ==== Program ==== |
| ==== Submit ==== | ==== Submit ==== |
| |
| Ok, so we have a program that works. Now we want to submit a dozen of them. In order to do that we will write a script that invokes this SAS program and hand it off to the scheduler (Lava). The scheduler will figure out which compute nodes are idle and submit your program on your behalf. | Ok, so now we have a program that works. Now we want to submit it maybe dozen times (maybe with different input data or different calculations, whatever). In order to do that we will write a shell script that invokes this SAS program and hands it off to the scheduler (Lava). The scheduler will figure out for us which compute nodes are idle and submit your programs on your behalf. |
| |
| * Create a shell script ''run'' for submission | * Create a shell script for example with the name ''run'' for submission |
| * Set execute permissions ''chmod u+x run'' | * Set execute permissions ''chmod u+x run'' |
| * Submit (see below) | * Submit (see below) |
| </code> | </code> |
| |
| The leading '#' is a comment in shell scripting but the scheduler specifically looks ofr leading '#BSUB' tags and interprets the line: -q (define queue), -J (job name), -o save STDOUT to a filename, -e same for STDERR. Then the job is defined as to what to run, here we prefix it with the unix utility time which reports run time to STDERR. | The leading '#' is a comment in shell scripting but the scheduler specifically looks for leading '#BSUB' tags and interprets the line: -q (define queue), -J (set job name), -o (save STDOUT to a filename), -e (same for STDERR). ''man bsub'' for more information. Then the job defines what to run, here we prefix it with the unix utility ''time'' which reports run time to STDERR. |
| |
| <code> | <code> |
| </code> | </code> |
| |
| And so the job was dispatched to host ''n10'' for execution. Results are posted in my home directory, in fact the entire job ran in my home directory on the remote compute node. I may not want to do that if I process or generate a lot of data. So we're going to add some statements to the script. Also, I may want to reserve some memory so the scheduler does not submit the job to hosts that have insufficient memory available or some other job is dispatched later that causes memory conflicts. | And so the job was dispatched to host ''n10'' for execution. Results are posted in my home directory, in fact the entire job ran in my home directory while on the remote compute node. I may not want to do that if I process or generate a lot of data. So we're going to add some statements to the script next. Also, I may want to reserve some memory so the scheduler does not submit the job to hosts that have insufficient memory available or some other job is dispatched later that causes memory conflicts with my job. |
| |
| The ''hp12'' is the greentail HP cluster where each compute node has 12 GB memory footprint. Memory footprints for the other queues differ, please consult this link (there is some old data...) [[http://petaltail.wesleyan.edu/cgi-bin/bqueues_web.cgi|http://petaltail.wesleyan.edu/cgi-bin/bqueues_web.cgi]] | The ''hp12'' queue is the cluster greentail's default queue where each compute node has a 12 GB memory footprint. Memory footprints of hosts for the other queues differ, please consult this link (there is some old data...) [[http://petaltail.wesleyan.edu/cgi-bin/bqueues_web.cgi|http://petaltail.wesleyan.edu/cgi-bin/bqueues_web.cgi]] for information about other queues. |
| | |
| | ==== Submit 2 ==== |
| | |
| | On the back end compute nodes, unless specified, the job runs inside your home directory. That job competes with other activities inside /home. Compute nodes have two other areas where the jobs could be submitted: /localscratch and /sanscratch. The former is a local filesystem for each node and should be used if file locking is essential. The later is a filesystem from greentails diskarray (5 TB) served vi IPoIB (that is NFS traffic over fast interconnects switches, the performance should be much better than gigabit ethernet switches). It is comprised of disks and spindles that are not impacted by what happens on /home. So we're going to use that. |
| | |
| | In the SAS program we add the following lines |
| | |
| | <code> |
| | %let jobpid = %sysget(LSB_JOBID); |
| | libname here "/sanscratch/&jobpid"; |
| | </code> |
| | |
| | And change this line to use local disks for storage |
| | |
| | <code> |
| | data here.one; |
| | </code> |
| | |
| | In the submission script we change the following |
| | |
| | * new submission file with edits |
| | * -n implies reserve job slots (cpu cores) for job (not necesssary, SAS jobs will always use only one) |
| | * -R reserves memory, for example, reserve 200 MB of memory on target compute node |
| | * scheduler creates unique dirs in scratch by JOBPID for you, so we'll stage the job there |
| | * but now we must copy relevant files //to// scratch dir and results back //to// home dir |
| | |
| | |
| | <code> |
| | |
| | #!/bin/bash |
| | # submit via 'bsub < run' |
| | |
| | #BSUB -q hp12 |
| | #BSUB -J test |
| | #BSUB -o stdout |
| | #BSUB -e stderr |
| | #BSUB -n 1 |
| | #BSUB -R "rusage[mem=200]" |
| | |
| | # unique job dir in scratch |
| | export MYSANSCRATCH=/sanscratch/$LSB_JOBID |
| | cd $MYSANSCRATCH |
| | |
| | cp ~/sas/test.dat ~/sas/test.sas . |
| | time sas test |
| | cp test.log test.lst ~/sas |
| | |
| | </code> |
| | |
| | |
| | * you can monitor the progress of your jobs from greentail while it runs |
| | |
| | <code> |
| | [hmeij@greentail sas]$ ll /sanscratch/492667/ |
| | total 16 |
| | -rw-r--r-- 1 hmeij its 33 Dec 21 14:31 test.dat |
| | -rw-r--r-- 1 hmeij its 2568 Dec 21 14:31 test.log |
| | -rw-r--r-- 1 hmeij its 258 Dec 21 14:31 test.lst |
| | -rw-r--r-- 1 hmeij its 140 Dec 21 14:31 test.sas |
| | </code> |
| | |
| | ==== Best Practices ==== |
| | |
| | * You may submit as many SAS jobs as you like, just leave enough resources available for others to also get work done |
| | * Because SAS submission are serial, non-parallel jobs your -n flag is always 1 |
| | * Reserve resources if you know what you need, especially memory |
| | * Use /sanscratch for large data jobs with heavy read/write operations |
| | * Queue ehwfd is preferentially for Gaussian users and stay off the stata and matlab queues please |
| | * Write smart SAS code, for example, use data set indexes and PROC SQL (this can be your best friend) |
| | * ... suggestions will be added to this page |
| |
| \\ | \\ |
| **[[cluster:0|Back]]** | **[[cluster:0|Back]]** |
