Jason, The array jobs are designed to behave like independent jobs (but are stored more efficiently internally to avoid straining the controller). So in principle slurm could schedule them one per node or multiple per node. The --nodes and --ntasks parameters apply to individual jobs in the array; thus setting --nodes=1 would definitely force jobs to run on different nodes.
The fact that they queue when forced to a single node is suspicious. Maybe you set up the partition as --exclusive? Or maybe jobs are requesting some other limited resource (e.g. if DefMemPerCPU is set to all the memory) preventing slurm from scheduling them simultaneously. If you're struggling with the array syntax, try just submitting two jobs to the same node and checking that you can get them to run simultaneously. Best of luck, -Spencer On 1 September 2020 at 18:50:30, Dana, Jason T. (jason.d...@jhuapl.edu) wrote: Hello, I am new to Slurm and I am working on setting up a cluster. I am testing out running a batch execution using an array and am seeing only one task executed in the array per node. Even if I specify in the sbatch command that only one node should be used, it executes a single task on each of the available nodes in the partition. I was under the impression that it would continue to execute tasks until the resources on the node or for the user were at their limit. Am I missing something or have I misinterpreted how sbatch and/or the job scheduling should work? Here is one of the commands I have run: sbatch --array=0-15 --partition=htc-amd --wrap 'python3 -c "import time; print(\"working\"); time.sleep(5)"' The htc-amd partition has 8 nodes and the results of this command are a single task being run on each node while the others are queued waiting for them to finish. As I mentioned before, if I specify --nodes=1 it will still execute a single task on every node in the partition. The only way I have gotten it to use on a single node was to use --nodelist, which worked but only to execute a single task and queued the rest. I have also tried specifying --ntasks and --ntasks-per-node. It appears to reserve resources, as I can cause it to hit the QOS core/cpu limit, but it does not affect the number of tasks executed on each node. Thank you for any help you can offer! Jason
