StochasticResults

This object is designed to work with the SamplerPostprocessorTransfer object for transferring data from a Postprocessor to a VectorPostprocessor on the master application.

Example Syntax

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = sample
    execute_on = 'INITIAL TIMESTEP_END'
  []
[]

/opt/civet/build_0/moose/modules/stochastic_tools/test/tests/transfers/sampler_postprocessor/master.i

[Mesh]
  type = GeneratedMesh
  dim = 1
  nx = 1
  ny = 1
[]

[Variables]
  [u]
  []
[]

[Distributions]
  [uniform_left]
    type = UniformDistribution
    lower_bound = 0
    upper_bound = 0.5
  []
  [uniform_right]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 2
  []
[]

[Samplers]
  [sample]
    type = SobolSampler
    num_rows = 3
    distributions = 'uniform_left uniform_right'
    execute_on = INITIAL # create random numbers on initial and use them for each timestep
  []
[]

[MultiApps]
  [sub]
    type = SamplerTransientMultiApp
    input_files = sub.i
    sampler = sample
    execute_on = 'INITIAL TIMESTEP_BEGIN'
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = sub
    sampler = sample
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
    execute_on = INITIAL
    check_multiapp_execute_on = false
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = sub
    sampler = sample
    to_vector_postprocessor = storage
    from_postprocessor = avg
    execute_on = TIMESTEP_BEGIN
    check_multiapp_execute_on = false
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = sample
    execute_on = 'INITIAL TIMESTEP_END'
  []
[]

[Executioner]
  type = Transient
  num_steps = 5
  dt = 0.01
[]

[Problem]
  solve = false
  kernel_coverage_check = false
[]

[Outputs]
  csv = true
[]

Input Parameters

contains_complete_historyFalseSet this flag to indicate that the values in all vectors declared by this VPP represent a time history (e.g. with each invocation, new values are added and old values are never removed). This changes the output so that only a single file is output and updated with each invocation
Default:False
C++ Type:bool
Options:
Description:Set this flag to indicate that the values in all vectors declared by this VPP represent a time history (e.g. with each invocation, new values are added and old values are never removed). This changes the output so that only a single file is output and updated with each invocation
execute_onTIMESTEP_ENDThe list of flag(s) indicating when this object should be executed, the available options include NONE, INITIAL, LINEAR, NONLINEAR, TIMESTEP_END, TIMESTEP_BEGIN, FINAL, CUSTOM.
Default:TIMESTEP_END
C++ Type:ExecFlagEnum
Options:NONE INITIAL LINEAR NONLINEAR TIMESTEP_END TIMESTEP_BEGIN FINAL CUSTOM
Description:The list of flag(s) indicating when this object should be executed, the available options include NONE, INITIAL, LINEAR, NONLINEAR, TIMESTEP_END, TIMESTEP_BEGIN, FINAL, CUSTOM.
output_distributed_rank4294967295When 'parallel_type = DISTRIBUTED' set this to copy the data from the specified processor for output. This is mainly for testing since the data from that rank will override the data on the root process.
Default:4294967295
C++ Type:unsigned int
Options:
Description:When 'parallel_type = DISTRIBUTED' set this to copy the data from the specified processor for output. This is mainly for testing since the data from that rank will override the data on the root process.
parallel_typeREPLICATEDSpecify if the stored data vector is replicated or distributed across processors.
Default:REPLICATED
C++ Type:MooseEnum
Options:REPLICATED DISTRIBUTED
Description:Specify if the stored data vector is replicated or distributed across processors.
samplersA list of sampler names of associated data.
C++ Type:std::vector
Options:
Description:A list of sampler names of associated data.

Optional Parameters

allow_duplicate_execution_on_initialFalseIn the case where this UserObject is depended upon by an initial condition, allow it to be executed twice during the initial setup (once before the IC and again after mesh adaptivity (if applicable).
Default:False
C++ Type:bool
Options:
Description:In the case where this UserObject is depended upon by an initial condition, allow it to be executed twice during the initial setup (once before the IC and again after mesh adaptivity (if applicable).
control_tagsAdds user-defined labels for accessing object parameters via control logic.
C++ Type:std::vector
Options:
Description:Adds user-defined labels for accessing object parameters via control logic.
enableTrueSet the enabled status of the MooseObject.
Default:True
C++ Type:bool
Options:
Description:Set the enabled status of the MooseObject.
force_preauxFalseForces the GeneralUserObject to be executed in PREAUX
Default:False
C++ Type:bool
Options:
Description:Forces the GeneralUserObject to be executed in PREAUX
outputsVector of output names were you would like to restrict the output of variables(s) associated with this object
C++ Type:std::vector
Options:
Description:Vector of output names were you would like to restrict the output of variables(s) associated with this object
use_displaced_meshFalseWhether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.
Default:False
C++ Type:bool
Options:
Description:Whether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.

Advanced Parameters

Input Files

modules/stochastic_tools/test/tests/transfers/sampler_postprocessor/errors/wrong_multi_app.i
modules/stochastic_tools/test/tests/vectorpostprocessors/stochastic_results/master.i
modules/stochastic_tools/test/tests/multiapps/batch_commandline_control/master_multiple.i
modules/stochastic_tools/examples/batch/transient.i
modules/stochastic_tools/test/tests/multiapps/batch_sampler_transient_multiapp/master_transient.i
modules/stochastic_tools/test/tests/transfers/sampler_postprocessor/master.i
modules/stochastic_tools/test/tests/multiapps/batch_full_solve_multiapp/master_full_solve.i
modules/stochastic_tools/test/tests/vectorpostprocessors/multiple_stochastic_results/master.i
modules/stochastic_tools/test/tests/multiapps/batch_commandline_control/master_single.i
modules/stochastic_tools/test/tests/vectorpostprocessors/stochastic_results_complete_history/master.i
modules/stochastic_tools/test/tests/transfers/batch_sampler_transfer/master.i
modules/stochastic_tools/examples/batch/full_solve.i

modules/stochastic_tools/test/tests/transfers/sampler_postprocessor/errors/wrong_multi_app.i

[Mesh]
  type = GeneratedMesh
  dim = 1
  nx = 1
  ny = 1
[]

[Variables]
  [u]
  []
[]

[Distributions]
  [uniform_left]
    type = UniformDistribution
    lower_bound = 0
    upper_bound = 0.5
  []
  [uniform_right]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 2
  []
[]

[Samplers]
  [sample]
    type = SobolSampler
    num_rows = 3
    distributions = 'uniform_left uniform_right'
    execute_on = INITIAL # create random numbers on initial and use them for each timestep
  []
[]

[MultiApps]
  [sub]
    type = TransientMultiApp
    input_files = sub.i
    positions = '0 0 0'
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = sub
    sampler = sample
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
    execute_on = INITIAL
    check_multiapp_execute_on = false
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = sub
    sampler = sample
    to_vector_postprocessor = storage
    from_postprocessor = avg
    execute_on = timestep_end
    check_multiapp_execute_on = false
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = sample
  []
[]

[Executioner]
  type = Transient
  num_steps = 5
  dt = 0.01
[]

[Problem]
  solve = false
  kernel_coverage_check = false
[]

[Outputs]
  csv = true
[]

modules/stochastic_tools/test/tests/vectorpostprocessors/stochastic_results/master.i

[Mesh]
  type = GeneratedMesh
  dim = 1
  nx = 1
  ny = 1
[]

[Variables]
  [u]
  []
[]

[Distributions]
  [uniform_left]
    type = UniformDistribution
    lower_bound = 0
    upper_bound = 0.5
  []
  [uniform_right]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 2
  []
[]

[Samplers]
  [sample]
    type = SobolSampler
    num_rows = 3
    distributions = 'uniform_left uniform_right'
    execute_on = INITIAL # create random numbers on initial and use them for each timestep
  []
[]

[MultiApps]
  [sub]
    type = SamplerTransientMultiApp
    input_files = sub.i
    sampler = sample
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = sub
    sampler = sample
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = sub
    sampler = sample
    to_vector_postprocessor = storage
    from_postprocessor = avg
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    parallel_type = DISTRIBUTED
    samplers = sample
  []
[]

[Executioner]
  type = Transient
  num_steps = 1
[]

[Problem]
  solve = false
  kernel_coverage_check = false
[]

[Outputs]
  [out]
    type = CSV
    execute_on = FINAL
  []
[]

modules/stochastic_tools/test/tests/multiapps/batch_commandline_control/master_multiple.i

[Mesh]
  type = GeneratedMesh
  dim = 1
[]

[Problem]
  type = FEProblem
  solve = false
[]

[Executioner]
  type = Steady
[]

[Distributions]
  [uniform]
    type = UniformDistribution
    lower_bound = 5
    upper_bound = 10
  []
[]

[Samplers]
  [sample]
    type = MonteCarloSampler
    num_rows = 3
    distributions = 'uniform uniform'
    execute_on = 'PRE_MULTIAPP_SETUP'
  []
[]

[MultiApps]
  [sub]
    type = SamplerFullSolveMultiApp
    sampler = sample
    input_files = 'sub.i'
  []
[]

[Transfers]
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = sub
    sampler = sample
    to_vector_postprocessor = storage
    from_postprocessor = size
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = sample
  []
[]

[Controls]
  [cmdline]
    type = MultiAppCommandLineControl
    multi_app = sub
    sampler = sample
    param_names = 'Mesh/xmax Mesh/ymax'
  []
[]

[Outputs]
  [out]
    type = CSV
    execute_on = FINAL
  []
[]

modules/stochastic_tools/examples/batch/transient.i

[Mesh]
  type = GeneratedMesh
  dim = 1
[]

[Problem]
  kernel_coverage_check = false
  solve = false
[]

[Distributions]
  [uniform]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 9
  []
[]

[Samplers]
  [mc]
    type = MonteCarloSampler
    n_samples = 10
    distributions = 'uniform uniform'
  []
[]

[Executioner]
  type = Transient
  num_steps = 10
[]

[MultiApps]
  [runner]
    type = SamplerFullSolveMultiApp
    sampler = mc
    input_files = 'sub.i'
    execute_on = 'INITIAL TIMESTEP_END'
    mode = batch-restore
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = runner
    parameters = 'BCs/left/value BCs/right/value'
    to_control = receiver
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = runner
    vector_postprocessor = storage
    postprocessor = average
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
  []
[]

[Postprocessors]
  [total]
    type = MemoryUsage
    execute_on = 'INITIAL TIMESTEP_END'
  []
  [per_proc]
    type = MemoryUsage
    value_type = "average"
    execute_on = 'INITIAL TIMESTEP_END'
  []
  [max_proc]
    type = MemoryUsage
    value_type = "max_process"
    execute_on = 'INITIAL TIMESTEP_END'
  []
[]

[Outputs]
  csv = true
  perf_graph = true
[]

modules/stochastic_tools/test/tests/multiapps/batch_sampler_transient_multiapp/master_transient.i

[Mesh]
  type = GeneratedMesh
  dim = 1
[]

[Problem]
  kernel_coverage_check = false
  solve = false
[]

[Distributions]
  [uniform]
    type = UniformDistribution
    lower_bound = 2
    upper_bound = 4
  []
[]

[Samplers]
  [mc]
    type = MonteCarloSampler
    num_rows = 5
    distributions = 'uniform uniform'
    execute_on = 'INITIAL TIMESTEP_BEGIN'
  []
[]

[Executioner]
  type = Transient
  num_steps = 3
[]

[MultiApps]
  [runner]
    type = SamplerTransientMultiApp
    sampler = mc
    input_files = 'sub.i'
    execute_on = 'INITIAL TIMESTEP_BEGIN'
    mode = batch-restore
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = runner
    sampler = mc
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = runner
    sampler = mc
    to_vector_postprocessor = storage
    from_postprocessor = average
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = mc
    execute_on = 'INITIAL TIMESTEP_END'
  []
[]

[Outputs]
  csv = true
[]

modules/stochastic_tools/test/tests/transfers/sampler_postprocessor/master.i

[Mesh]
  type = GeneratedMesh
  dim = 1
  nx = 1
  ny = 1
[]

[Variables]
  [u]
  []
[]

[Distributions]
  [uniform_left]
    type = UniformDistribution
    lower_bound = 0
    upper_bound = 0.5
  []
  [uniform_right]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 2
  []
[]

[Samplers]
  [sample]
    type = SobolSampler
    num_rows = 3
    distributions = 'uniform_left uniform_right'
    execute_on = INITIAL # create random numbers on initial and use them for each timestep
  []
[]

[MultiApps]
  [sub]
    type = SamplerTransientMultiApp
    input_files = sub.i
    sampler = sample
    execute_on = 'INITIAL TIMESTEP_BEGIN'
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = sub
    sampler = sample
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
    execute_on = INITIAL
    check_multiapp_execute_on = false
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = sub
    sampler = sample
    to_vector_postprocessor = storage
    from_postprocessor = avg
    execute_on = TIMESTEP_BEGIN
    check_multiapp_execute_on = false
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = sample
    execute_on = 'INITIAL TIMESTEP_END'
  []
[]

[Executioner]
  type = Transient
  num_steps = 5
  dt = 0.01
[]

[Problem]
  solve = false
  kernel_coverage_check = false
[]

[Outputs]
  csv = true
[]

modules/stochastic_tools/test/tests/multiapps/batch_full_solve_multiapp/master_full_solve.i

[Mesh]
  type = GeneratedMesh
  dim = 1
[]

[Problem]
  kernel_coverage_check = false
  solve = false
[]

[Distributions]
  [uniform_0]
    type = UniformDistribution
    lower_bound = 0.1
    upper_bound = 0.3
  []
[]

[Samplers]
  [mc]
    type = MonteCarloSampler
    num_rows = 5
    distributions = 'uniform_0'
  []
[]

[Executioner]
  type = Steady
[]

[MultiApps]
  [runner]
    type = SamplerFullSolveMultiApp
    sampler = mc
    input_files = 'sub.i'
    mode = batch-reset
  []
[]

[Transfers]
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = runner
    sampler = mc
    to_vector_postprocessor = storage
    from_postprocessor = average
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = mc
  []
[]

[Outputs]
  csv = true
  execute_on = 'FINAL'
[]

modules/stochastic_tools/test/tests/vectorpostprocessors/multiple_stochastic_results/master.i

[Mesh]
  type = GeneratedMesh
  dim = 1
  nx = 1
  ny = 1
[]

[Variables]
  [u]
  []
[]

[Distributions]
  [uniform_left]
    type = UniformDistribution
    lower_bound = 0
    upper_bound = 0.5
  []
  [uniform_right]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 2
  []
[]

[Samplers]
  [sobol]
    type = SobolSampler
    num_rows = 3
    distributions = 'uniform_left uniform_right'
    execute_on = INITIAL # create random numbers on initial and use them for each timestep
  []
  [mc]
    type = MonteCarloSampler
    num_rows = 5
    distributions = 'uniform_left uniform_right'
    execute_on = INITIAL # create random numbers on initial and use them for each timestep
  []
[]

[MultiApps]
  [sobol]
    type = SamplerTransientMultiApp
    input_files = sub.i
    sampler = sobol
  []
  [mc]
    type = SamplerTransientMultiApp
    input_files = sub.i
    sampler = mc
  []
[]

[Transfers]
  [sobol]
    type = SamplerParameterTransfer
    multi_app = sobol
    sampler = sobol
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
  []
  [sobol_data]
    type = SamplerPostprocessorTransfer
    multi_app = sobol
    sampler = sobol
    to_vector_postprocessor = storage
    from_postprocessor = avg
  []

  [mc]
    type = SamplerParameterTransfer
    multi_app = mc
    sampler = mc
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
  []
  [mc_data]
    type = SamplerPostprocessorTransfer
    multi_app = mc
    sampler = mc
    to_vector_postprocessor = storage
    from_postprocessor = avg
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    parallel_type = REPLICATED
    samplers = 'sobol mc'
  []
[]

[Executioner]
  type = Transient
  num_steps = 1
[]

[Problem]
  solve = false
  kernel_coverage_check = false
[]

[Outputs]
  [out]
    type = CSV
    execute_on = FINAL
  []
[]

modules/stochastic_tools/test/tests/multiapps/batch_commandline_control/master_single.i

[Mesh]
  type = GeneratedMesh
  dim = 1
[]

[Problem]
  type = FEProblem
  solve = false
[]

[Executioner]
  type = Steady
[]

[Distributions]
  [uniform]
    type = UniformDistribution
    lower_bound = 5
    upper_bound = 10
  []
[]

[Samplers]
  [sample]
    type = MonteCarloSampler
    num_rows = 3
    distributions = 'uniform'
    execute_on = 'PRE_MULTIAPP_SETUP'
  []
[]

[MultiApps]
  [sub]
    type = SamplerFullSolveMultiApp
    sampler = sample
    input_files = 'sub.i'
    mode = batch-reset
  []
[]

[Transfers]
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = sub
    sampler = sample
    to_vector_postprocessor = storage
    from_postprocessor = size
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = sample
  []
[]

[Controls]
  [cmdline]
    type = MultiAppCommandLineControl
    multi_app = sub
    sampler = sample
    param_names = 'Mesh/xmax'
  []
[]

[Outputs]
  [out]
    type = CSV
    execute_on = FINAL
  []
[]

modules/stochastic_tools/test/tests/vectorpostprocessors/stochastic_results_complete_history/master.i

[Mesh]
  type = GeneratedMesh
  dim = 1
  nx = 1
  ny = 1
[]

[Variables]
  [u]
  []
[]

[Distributions]
  [uniform_left]
    type = UniformDistribution
    lower_bound = 0
    upper_bound = 0.5
  []
  [uniform_right]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 2
  []
[]

[Samplers]
  [sample]
    type = MonteCarloSampler
    num_rows = 3
    distributions = 'uniform_left uniform_right'
    execute_on = 'INITIAL TIMESTEP_BEGIN'
  []
[]

[MultiApps]
  [sub]
    type = SamplerTransientMultiApp
    input_files = sub.i
    sampler = sample
    execute_on = 'INITIAL TIMESTEP_BEGIN'
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = sub
    sampler = sample
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = sub
    sampler = sample
    to_vector_postprocessor = storage
    from_postprocessor = avg
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    parallel_type = REPLICATED
    samplers = sample
    contains_complete_history = true
    execute_on = 'INITIAL TIMESTEP_END'
  []
[]

[Executioner]
  type = Transient
  num_steps = 2
[]

[Problem]
  solve = false
  kernel_coverage_check = false
[]

[Outputs]
  [out]
    type = CSV
  []
[]

modules/stochastic_tools/test/tests/transfers/batch_sampler_transfer/master.i

[Mesh]
  type = GeneratedMesh
  dim = 1
[]

[Problem]
  kernel_coverage_check = false
  solve = false
[]

[Distributions]
  [uniform_0]
    type = UniformDistribution
    lower_bound = 100
    upper_bound = 200
  []
  [uniform_1]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 2
  []
[]

[Samplers]
  [mc]
    type = MonteCarloSampler
    num_rows = 15
    distributions = 'uniform_0 uniform_1'
    execute_on = INITIAL
  []
[]

[Executioner]
  type = Steady
[]

[MultiApps]
  [runner]
    type = SamplerFullSolveMultiApp
    sampler = mc
    input_files = 'sub.i'
    mode = batch-reset
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = runner
    sampler = mc
    parameters = 'BCs/left/value BCs/right/value'
    to_control = 'stochastic'
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = runner
    sampler = mc
    to_vector_postprocessor = storage
    from_postprocessor = average
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
    samplers = mc
    execute_on = 'INITIAL TIMESTEP_END'
  []
  [data]
    type = SamplerData
    sampler = mc
  []
[]

[Outputs]
  csv = true
  execute_on = 'TIMESTEP_END'
[]

modules/stochastic_tools/examples/batch/full_solve.i

[Mesh]
  type = GeneratedMesh
  dim = 1
[]

[Problem]
  kernel_coverage_check = false
  solve = false
[]

[Distributions]
  [uniform]
    type = UniformDistribution
    lower_bound = 1
    upper_bound = 9
  []
[]

[Samplers]
  [mc]
    type = MonteCarloSampler
    n_samples = 10
    distributions = 'uniform uniform'
  []
[]

[Executioner]
  type = Steady
[]

[MultiApps]
  [runner]
    type = SamplerFullSolveMultiApp
    sampler = mc
    input_files = 'sub.i'
    mode = batch-restore
  []
[]

[Transfers]
  [runner]
    type = SamplerParameterTransfer
    multi_app = runner
    parameters = 'BCs/left/value BCs/right/value'
    to_control = receiver
  []
  [data]
    type = SamplerPostprocessorTransfer
    multi_app = runner
    vector_postprocessor = storage
    postprocessor = average
  []
[]

[VectorPostprocessors]
  [storage]
    type = StochasticResults
  []
[]

[Postprocessors]
  [total]
    type = MemoryUsage
    execute_on = 'INITIAL TIMESTEP_END'
  []
  [per_proc]
    type = MemoryUsage
    value_type = "average"
    execute_on = 'INITIAL TIMESTEP_END'
  []
  [max_proc]
    type = MemoryUsage
    value_type = "max_process"
    execute_on = 'INITIAL TIMESTEP_END'
  []
[]

[Outputs]
  csv = true
  perf_graph = true
[]

Example Syntax
Input Parameters
Input Files

Application Usage

Physics and Syntax

Application Development

Framework Development

MOOSEDocs

Infrastructure

Questions

Information and Tools

StochasticResults

Example Syntax

Input Parameters

Optional Parameters

Advanced Parameters

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