NodeDescriptor

pydantic model qcengine.config.NodeDescriptor

Description of an individual node

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{
   "title": "NodeDescriptor",
   "description": "Description of an individual node",
   "type": "object",
   "properties": {
      "hostname_pattern": {
         "title": "Hostname Pattern",
         "type": "string"
      },
      "name": {
         "title": "Name",
         "type": "string"
      },
      "scratch_directory": {
         "title": "Scratch Directory",
         "type": "string"
      },
      "memory": {
         "title": "Memory",
         "type": "number"
      },
      "memory_safety_factor": {
         "title": "Memory Safety Factor",
         "default": 10,
         "type": "integer"
      },
      "ncores": {
         "title": "Ncores",
         "description": "Number of cores accessible to each task on this node\n    \n    The default value, ``None``, will allow QCEngine to autodetect the number of cores.",
         "type": "integer"
      },
      "jobs_per_node": {
         "title": "Jobs Per Node",
         "default": 1,
         "type": "integer"
      },
      "retries": {
         "title": "Retries",
         "default": 0,
         "type": "integer"
      },
      "is_batch_node": {
         "title": "Is Batch Node",
         "default": false,
         "help": "Whether the node running QCEngine is a batch node\n    \n    Some clusters are configured such that tasks are launched from a special \"batch\" or \"MOM\" onto the compute nodes.\n    The compute nodes on such clusters often have a different CPU architecture than the batch nodes and \n    often are unable to launch MPI tasks, which has two implications:\n        1) QCEngine must make *all* calls to an executable via ``mpirun`` because the executables might not\n        be able to run on the batch node. \n        2) QCEngine must run on the batch node to be able to launch tasks on the more than one compute nodes  \n    \n    ``is_batch_node`` is used when creating the task configuration as a means of determining whether\n    ``mpiexec_command`` must always be used even for serial jobs (e.g., getting the version number)\n    ",
         "type": "boolean"
      },
      "mpiexec_command": {
         "title": "Mpiexec Command",
         "description": "Invocation for launching node-parallel tasks with MPI\n        \n        The invocation need not specify the number of nodes, tasks, or cores per node.\n        Information about the task configuration will be added to the command by use of\n        Python's string formatting. The configuration will be supplied as the following variables:\n        \n            {nnodes} - Number of nodes\n            {ranks_per_node} - Number of MPI ranks per node\n            {cores_per_rank} - Number of cores to use for each MPI rank\n            {total_ranks} - Total number of MPI ranks\n            \n        As examples, the ``aprun`` command on Cray systems should be similar to \n        ``aprun -n {total_ranks} -N {ranks_per_node}`` and ``mpirun`` from OpenMPI should\n        be similar to ``mpirun -np {total_ranks} -N {ranks_per_node}``.\n        \n        Programs where each MPI rank can use multiple threads (e.g., QC programs with MPI+OpenMP) can \n        use the {cores_per_rank} option to control the hybrid parallelism. \n        As an example, the Cray ``aprun`` command using this figure could be:\n        ``aprun -n {total_ranks} -N {ranks_per_node} -d {cores_per_rank} -j 1``.\n        The appropriate number of ranks per node will be determined based on the number of\n        cores per node and the number of cores per rank.\n        ",
         "type": "string"
      }
   },
   "required": [
      "hostname_pattern",
      "name"
   ],
   "additionalProperties": false
}

Fields:

• hostname_pattern (str)

• is_batch_node (bool)

• jobs_per_node (int)

• memory (float | None)

• memory_safety_factor (int)

• mpiexec_command (str | None)

• name (str)

• ncores (int | None)

• retries (int)

• scratch_directory (str | None)

field hostname_pattern: str [Required]

field is_batch_node: bool = False

field jobs_per_node: int = 1

field memory: Optional[float] = None

field memory_safety_factor: int = 10

field mpiexec_command: Optional[str] = None

Invocation for launching node-parallel tasks with MPI

The invocation need not specify the number of nodes, tasks, or cores per node. Information about the task configuration will be added to the command by use of Python’s string formatting. The configuration will be supplied as the following variables:

{nnodes} - Number of nodes {ranks_per_node} - Number of MPI ranks per node {cores_per_rank} - Number of cores to use for each MPI rank {total_ranks} - Total number of MPI ranks

As examples, the aprun command on Cray systems should be similar to aprun -n {total_ranks} -N {ranks_per_node} and mpirun from OpenMPI should be similar to mpirun -np {total_ranks} -N {ranks_per_node}.

Programs where each MPI rank can use multiple threads (e.g., QC programs with MPI+OpenMP) can use the {cores_per_rank} option to control the hybrid parallelism. As an example, the Cray aprun command using this figure could be: aprun -n {total_ranks} -N {ranks_per_node} -d {cores_per_rank} -j 1. The appropriate number of ranks per node will be determined based on the number of cores per node and the number of cores per rank.

field name: str [Required]

field ncores: Optional[int] = None

Number of cores accessible to each task on this node

The default value, None, will allow QCEngine to autodetect the number of cores.

field retries: int = 0

field scratch_directory: Optional[str] = None