estimate_simulation_RAM

tenpy.simulations.simulation.estimate_simulation_RAM(*, suppress_non_RAM_output=True, RAM_output_unit=None, estimate_RAM_const_offset=(100, 'MB'), **simulation_params)[source]

Pre-simulation RAM estimate.

Large-scale simulations need to be submitted to a simulation cluster, which often requires to give an estimate of the required RAM before actually running the simulation.

See also the model parameter Model.mem_saving_factor.

Parameters:
  • suppress_non_RAM_output (bool) – If True (default), suppress all other output (except for error messages).

  • RAM_output_unit (None | str) – Memory unit to be used for the output. None defaults to human-readable rounding.

  • estimate_RAM_const_offset ((int, str)) – Defaults to (100, "MB") which gets added to the scaling estimates. This constant needs to account for loading python libraries etc.

  • **simulation_params – Other simulation parameters as they would be pass to run_simulation() to run the simulation.

Returns:

  • estimate (float) – Estimated RAM requirements including the estimate_RAM_const_offset.

  • unit (str) – Unit of the estimate

See also

Simulation.estimate_RAM

Corresponding simulation method

tenpy.algorithms.algorithm.Algorithm.estimate_RAM

corresponding algorithm method.