The batch scheduler is configured with a number of scheduling policies to keep in mind. The policies attempt to balance the competing objectives of reasonable queue wait times and efficient system utilization. The details of these policies differ slightly on each system. Exceptions to the limits can be made under certain circumstances; contact oschelp@osc.edu for details.
Several commands allow you to check job status, monitor execution, collect performance statistics or even delete your job, if necessary.
There are many possible reasons for a long queue wait — read on to learn how to check job status and for more about how job scheduling works.
Use the squeue command to check the status of your jobs, including whether your job is queued or running and information about requested resources. If the job is running, you can view elapsed time and resources used.
CUDA™ (Compute Unified Device Architecture) is a parallel computing platform and programming model developed by Nvidia that enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).
Job scripts are submitted to the batch system using the sbatch command. Be sure to submit your job on the system you want your job to run on, or use the --cluster=<system> option to specify one.
Most jobs on our system are submitted as scripts with no command-line options. If your script is in a file named myscript:
sbatch myscript
In response to this command you’ll see a line with your job ID:
Intel Math Kernel Library (MKL) consists of high-performance, multithreaded mathematics libraries for linear algebra, fast Fourier transforms, vector math, and more.
