Changes between Version 16 and Version 17 of discovery

Timestamp:

04/28/23 13:00:00 (2 years ago)

Author:

badgeley

Comment:

--

discovery

@@ -179 +179 @@
 }}}
 
-
 to have a job of 8 cores on one node. 
 See cluster details: [[https://services.dartmouth.edu/TDClient/1806/Portal/KB/ArticleDet?ID=134058]].
+
+Each node has it's own time limit for jobs that are being run from the queue, but they tend to be 10 or 30 days. 
+You can find the time limit of each node by entering on Discovery:
+{{{
+#!sh
+sinfo
+}}}
+If you are running something interactively on Discovery, there may be a credential limit for the DartFS system of 10 hours. 
+Read more here: [[https://services.dartmouth.edu/TDClient/1806/Portal/KB/ArticleDet?ID=76691]]
+
+Now if you want to check the status of your job and the node you are using, type in the bash with the Discovery session:
+ {{{
+#!sh
+squeue -u username
+}}}
+
+You can delete your job manually by typing:
+
+{{{
+#!sh
+scancel JOBID
+}}}
+
+where `JOBID` is the ID of your job (indicated in the Matlab session). Matlab indicates too the directory of your job where you can find the files `JOBNAME.outlog` and `JOBNAME.errlog`. The outlog file contains the information that would appear if you were running your job on your local machine and the errlog file contains the error information in case the job encounters an error. 
+
+If you want to load results from the cluster manually (for example if you have an error due to an internet interruption), you find in the information Matlab gave you `$ISSM_DIR/execution/LAUNCHSTRING/JOBNAME.lock`, you copy the LAUNCHSTRING and you type in Matlab:
+
+{{{
+#!m
+md=loadresultsfromcluster(md,'LAUNCHSTRING','JOBNAME');
+}}}
+
+Obs.: in the case where `md.settings.waitonlock`>0 and you need to load manually (e.g., internet interruption), it is necessary to set `md.private.runtimename=LAUNCHSTRING;` before calling `loadresultsfromcluster`.
+
+
+== Other notes about running on Discovery  ==
 
 If you want to use more than one node (not recommended), the current (temporary) solution is to:\\
@@ -200 +235 @@
 If you do not do this, then your job will run on just one node.
 
-There is no specific time limit on Discovery, however, jobs longer than 10 hours may need credential to DartFS system. 
-Read more here: [[https://services.dartmouth.edu/TDClient/1806/Portal/KB/ArticleDet?ID=76691]]
-
-
-Now if you want to check the status of your job and the node you are using, type in the bash with the Discovery session:
- {{{
-#!sh
-squeue -u username
-}}}
-
-You can delete your job manually by typing:
-
-{{{
-#!sh
-scancel JOBID
-}}}
-
-where `JOBID` is the ID of your job (indicated in the Matlab session). Matlab indicates too the directory of your job where you can find the files `JOBNAME.outlog` and `JOBNAME.errlog`. The outlog file contains the information that would appear if you were running your job on your local machine and the errlog file contains the error information in case the job encounters an error. 
-
 To get more information about your job while it's running, from Discovery you can `ssh` into the node given by `squeue -u username` and then run `htop`. Once in `htop`, if you want to see information for a specific user, type `u` and then start typing the user ID until the correct one is highlighted and hit ENTER. 
 You can also get more information about a job by entering:
@@ -226 +242 @@
 }}}
 
-If you want to load results from the cluster manually (for example if you have an error due to an internet interruption), you find in the information Matlab gave you `$ISSM_DIR/execution/LAUNCHSTRING/JOBNAME.lock`, you copy the LAUNCHSTRING and you type in Matlab:
-
-{{{
-#!m
-md=loadresultsfromcluster(md,'LAUNCHSTRING','JOBNAME');
-}}}
-
-Obs.: in the case where `md.settings.waitonlock`>0 and you need to load manually (e.g., internet interruption), it is necessary to set `md.private.runtimename=LAUNCHSTRING;` before calling `loadresultsfromcluster`.
+If your job is in the queue for a long time, there may be several reasons for this. One thing to try is to add the following line to your `<run_name>.queue` file and restarting your job:
+{{{
+#!sh
+#SBATCH --partition preemptable
+}}}
+This may give you access to some idle nodes, but note that your job can be stopped if a higher priority job wants your resources.
+
 
 == slurm ==