Slurm Services

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Revision as of 10:10, 31 August 2021 by Boris (talk | contribs)
Contents
  1. Documentation for creating SLURM Workload Manager
  2. Example by executing a simple script



Documentation for creating SLURM Workload Manager

Creating a scheduler in a heterogeneous cluster environment covers the following: First it is necessary to define which will be the main (master) node that will properly forward the user-defined scripts in the form of jobs to the defined machines in the cluster. There are several different platforms for creating a cluster environment, in this document SLURM Workload Manager will be discussed. Advantages of using Slurm as a task environment are:

  • Support for high cluster systems and multiprocessor tasks - The SLURM environment enables the start-up, execution and monitoring of parallel tasks implemented via Message Passing Interface (MPI), on part of the allocated nodes as well as allowing efficient use of resources (nodes) according to a specific policy users,
  • Task profiling - Periodically review each resource assigned to a specific task (CPU runtime, RAM, power consumption, network resources, and disk space usage),
  • Support for MapReduce + algorithm,
  • Support for creating a sequence of tasks, ie one task can be divided into several sub-tasks that are performed in parallel for more efficient use of the given resources,
  • Database integration - where all user parameters and settings are stored,
  • Use of graphic resources to perform tasks - A large number of optional possibilities for additional use of graphic resources given to a specific task / tasks in order to better perform advanced algorithms in the field of machine learning.