Differences

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--- techstaff:slurm [2016/05/09 15:06] – kauffman
+++ techstaff:slurm [2017/07/27 11:23] – kauffman
@@ Line 1: / Line 1: @@
-====== DRAFT | Peanut Job Submission Cluster ======
+===== Notice =====
+Please use 'liverpool.cs.uchicago.edu' to submit your jobs. The SLURM cluster has not been upgraded to 16.04 yet.
-We are currently **alpha** testing and gauging user interest in a cluster of machines that allows for the submission of long running compute jobs. Think of these machines as a dumping ground for discrete computing tasks that might have been rude or disruptive to execute on the main (shared) shell servers (i.e., linux1, linux2, linux3).
+====== Peanut Job Submission Cluster ======
+We are currently **alpha** testing and gauging user interest in a cluster of machines that allows for the submission of long running compute jobs. Think of these machines as a dumping ground for discrete computing tasks that might be rude or disruptive to execute on the main (shared) shell servers (i.e., linux1, linux2, linux3).
 For job submission we will be using a piece of software called [[http://slurm.schedmd.com|SLURM]]. Simply put, SLURM is a queue management system and stands for **S**imple **L**inux **U**tility for **R**esource **M**anagement; it was developed at the Lawrence Livermore National Lab. It currently supports some of the largest compute clusters in the world. The best description of SLURM can be found on its homepage:
@@ Line 228: / Line 232: @@
 ====== Using the GPU ======
+===== Paths =====
+You will need to add the following to your $PATH and $LD_LIBRARY_PATH.
+  export PATH=$PATH:/usr/local/cuda/bin
+  export LD_LIBRARY_PATH=$LD_LIBRARY_PATH=/usr/local/cuda/lib
 ===== Example =====
 This sbatch script will get device information from the installed Tesla gpu.
@@ Line 240: / Line 251: @@
 #SBATCH --partition=gpu
 #SBATCH --job-name=get_tesla_info
+export PATH=$PATH:/usr/local/cuda/bin
+export LD_LIBRARY_PATH=$LD_LIBRARY_PATH=/usr/local/cuda/lib
 cat << EOF > /tmp/getinfo.cu
@@ Line 268: / Line 282: @@
 rm /tmp/getinfo.cu
 </code>
+==== Output ====
+STDOUT will look something like this:
+<code>
+cnetid@linux1:~$ cat $HOME/slurm/slurm_out/12567.gpu1.stdout
+Device Number: 0
+  Device name: Tesla M2090
+  Memory Clock Rate (KHz): 1848000
+  Memory Bus Width (bits): 384
+  Peak Memory Bandwidth (GB/s): 177.408000
+</code>
+STDERR should be blank.
 ====== More ======
 If you feel this documentation is lacking in some way please let techstaff know. Email [[techstaff@cs.uchicago.edu]], call (773-702-1031), or stop by our office (Ryerson 154).