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Add config options for adaptivity metrics and memory usage output to allow for different levels (#172)
* Add a config option for adaptivity output type of either local, global, or all * Modify memory usage output configuration to have levels and also an output frequency * Add CHANGELOG entry * Change wording in documentation
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‎CHANGELOG.md‎

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@@ -2,6 +2,7 @@
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## latest
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- Add config options for adaptivity metrics and memory usage output to allow for different levels https://github.com/precice/micro-manager/pull/172
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- Fix bug in adaptivity computation when an active simulation with associations is deactivated https://github.com/precice/micro-manager/pull/171
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- Properly handle micro simulation initialization for lazy initialization https://github.com/precice/micro-manager/pull/169
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- Delete the simulation object when the simulation is deactivated https://github.com/precice/micro-manager/pull/167

‎docs/configuration.md‎

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@@ -30,13 +30,16 @@ The Micro Manager is configured with a JSON file. An example configuration file
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This example configuration file is in [`examples/micro-manager-config.json`](https://github.com/precice/micro-manager/tree/develop/examples/micro-manager-config.json).
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The path to the file containing the Python importable micro simulation class is specified in the `micro_file_name` parameter. If the file is not in the working directory, give the relative path from the directory where the Micro Manager is executed.
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## Micro Manager Configuration
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Set the output [log](tooling-micro-manager-logging.html) directory using the parameter `output_dir`.
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To output the runtime memory usage, set `output_memory_usage` to `True`. This will output a CSV file with the peak memory usage (RSS) in every time window, in MBs.
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Parameter | Description
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--- | ---
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`micro_file_name` | Path to the file containing the Python importable micro simulation class. If the file is not in the working directory, give the relative path from the directory where the Micro Manager is executed.
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`output_directory` | Path to output directory for logging and performance metrics. Directory is created if not existing already.
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`memory_usage_output_type` | Set to either `local`, `global`, or `all`. `local` outputs rank-wise peak memory usage. `global` outputs global averaged peak memory usage. `all` outputs both local and global levels. All output is to a CSV file with the peak memory usage (RSS) in every time window, in MBs.
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`memory_usage_output_n` | Frequency of output of memory usage (integer which is number of time windows).
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There are three main sections in the configuration file, the `coupling_params`, the `simulation_params` and the optional `diagnostics`.
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Apart from the base settings, there are three main sections in the configuration file, the `coupling_params`, the `simulation_params` and the optional `diagnostics`.
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## Coupling Parameters
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@@ -120,6 +123,7 @@ Parameter | Description
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`type` | Set to either `local` or `global`. The type of adaptivity matters when the Micro Manager is run in parallel. `local` means comparing micro simulations within a local partitioned domain for similarity. `global` means comparing micro simulations from all partitions, so over the entire domain.
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`data` | List of names of data which are to be used to calculate if micro-simulations are similar or not. For example `["temperature", "porosity"]`.
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`adaptivity_every_n_time_windows` | Frequency of adaptivity computation (integer which is number of time windows).
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`output_type` | Set to either `local`, `global`, or `all`. `local` outputs rank-wise adaptivity metrics. `global` outputs global averaged metrics. `all` outputs both local and global metrics.
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`output_n` | Frequency of output of adaptivity metrics (integer which is number of time windows).
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`history_param` | History parameter $$ \Lambda $$, set as $$ \Lambda >= 0 $$.
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`coarsening_constant` | Coarsening constant $$ C_c $$, set as $$ 0 =< C_c < 1 $$.

‎micro_manager/adaptivity/adaptivity.py‎

Lines changed: 15 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -31,6 +31,7 @@ def __init__(self, configurator, rank, nsims) -> None:
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self._hist_param = configurator.get_adaptivity_hist_param()
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self._adaptivity_data_names = configurator.get_data_for_adaptivity()
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self._adaptivity_type = configurator.get_adaptivity_type()
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self._adaptivity_output_type = configurator.get_adaptivity_output_type()
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self._micro_problem = getattr(
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importlib.import_module(
@@ -74,7 +75,10 @@ def __init__(self, configurator, rank, nsims) -> None:
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else:
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metrics_output_dir = "adaptivity-metrics"
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77-
if self._rank == 0:
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if self._rank == 0 and (
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self._adaptivity_output_type == "global"
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or self._adaptivity_output_type == "all"
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):
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self._global_metrics_logger = Logger(
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"global-metrics-logger",
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metrics_output_dir + "-global.csv",
@@ -86,12 +90,16 @@ def __init__(self, configurator, rank, nsims) -> None:
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"n,avg active,avg inactive,max active,max inactive"
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)
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self._metrics_logger = Logger(
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"metrics-logger",
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metrics_output_dir + "-" + str(rank) + ".csv",
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rank,
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csv_logger=True,
94-
)
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if (
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self._adaptivity_output_type == "local"
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or self._adaptivity_output_type == "all"
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):
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self._metrics_logger = Logger(
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"metrics-logger",
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metrics_output_dir + "-" + str(rank) + ".csv",
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rank,
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csv_logger=True,
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)
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def _update_similarity_dists(self, dt: float, data: dict) -> None:
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"""

‎micro_manager/adaptivity/global_adaptivity.py‎

Lines changed: 45 additions & 29 deletions
Original file line numberDiff line numberDiff line change
@@ -65,7 +65,11 @@ def __init__(
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self._precice_participant = participant
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self._metrics_logger.log_info("n,n active,n inactive,assoc ranks")
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if (
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self._adaptivity_output_type == "all"
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or self._adaptivity_output_type == "local"
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):
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self._metrics_logger.log_info("n,n active,n inactive,assoc ranks")
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def compute_adaptivity(
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self,
@@ -168,7 +172,7 @@ def log_metrics(self, n: int) -> None:
168172
"""
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Log the following metrics:
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Metrics on this rank:
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Local metrics:
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- Time window at which the metrics are logged
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- Number of active simulations
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- Number of inactive simulations
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else:
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inactive_sims_on_this_rank += 1
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197-
ranks_of_sims = self._get_ranks_of_sims()
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if (
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self._adaptivity_output_type == "all"
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or self._adaptivity_output_type == "local"
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):
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ranks_of_sims = self._get_ranks_of_sims()
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assoc_ranks = [] # Ranks to which inactive sims on this rank are associated
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for global_id in self._global_ids:
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if not self._is_sim_active[global_id]:
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assoc_rank = int(
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ranks_of_sims[self._sim_is_associated_to[global_id]]
212+
)
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if not assoc_rank in assoc_ranks:
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assoc_ranks.append(assoc_rank)
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assoc_ranks = [] # Ranks to which inactive sims on this rank are associated
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for global_id in self._global_ids:
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if not self._is_sim_active[global_id]:
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assoc_rank = int(ranks_of_sims[self._sim_is_associated_to[global_id]])
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if not assoc_rank in assoc_ranks:
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assoc_ranks.append(assoc_rank)
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self._metrics_logger.log_info(
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"{},{},{},{}".format(
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n,
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active_sims_on_this_rank,
210-
inactive_sims_on_this_rank,
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assoc_ranks,
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self._metrics_logger.log_info(
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"{},{},{},{}".format(
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n,
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active_sims_on_this_rank,
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inactive_sims_on_this_rank,
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assoc_ranks,
222+
)
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)
213-
)
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215-
active_sims_rankwise = self._comm.gather(active_sims_on_this_rank, root=0)
216-
inactive_sims_rankwise = self._comm.gather(inactive_sims_on_this_rank, root=0)
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if (
226+
self._adaptivity_output_type == "all"
227+
or self._adaptivity_output_type == "global"
228+
):
229+
active_sims_rankwise = self._comm.gather(active_sims_on_this_rank, root=0)
230+
inactive_sims_rankwise = self._comm.gather(
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inactive_sims_on_this_rank, root=0
232+
)
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218-
if self._rank == 0:
219-
size = self._comm.Get_size()
234+
if self._rank == 0:
235+
size = self._comm.Get_size()
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221-
self._global_metrics_logger.log_info(
222-
"{},{},{},{},{}".format(
223-
n,
224-
sum(active_sims_rankwise) / size,
225-
sum(inactive_sims_rankwise) / size,
226-
max(active_sims_rankwise),
227-
max(inactive_sims_rankwise),
237+
self._global_metrics_logger.log_info(
238+
"{},{},{},{},{}".format(
239+
n,
240+
sum(active_sims_rankwise) / size,
241+
sum(inactive_sims_rankwise) / size,
242+
max(active_sims_rankwise),
243+
max(inactive_sims_rankwise),
244+
)
228245
)
229-
)
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def _communicate_micro_output(
232248
self,

‎micro_manager/adaptivity/local_adaptivity.py‎

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Original file line numberDiff line numberDiff line change
@@ -32,7 +32,11 @@ def __init__(self, configurator, num_sims, participant, rank, comm) -> None:
3232
super().__init__(configurator, rank, num_sims)
3333
self._comm = comm
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35-
self._metrics_logger.log_info("n,n active,n inactive")
35+
if (
36+
self._adaptivity_output_type == "all"
37+
or self._adaptivity_output_type == "local"
38+
):
39+
self._metrics_logger.log_info("n,n active,n inactive")
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3741
self._precice_participant = participant
3842

@@ -129,7 +133,7 @@ def log_metrics(self, n: int) -> None:
129133
"""
130134
Log the following metrics:
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Metrics on this rank:
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Local metrics:
133137
- Time window at which the metrics are logged
134138
- Number of active simulations
135139
- Number of inactive simulations
@@ -153,29 +157,39 @@ def log_metrics(self, n: int) -> None:
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else:
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inactive_sims_on_this_rank += 1
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156-
self._metrics_logger.log_info(
157-
"{},{},{}".format(
158-
n,
159-
active_sims_on_this_rank,
160-
inactive_sims_on_this_rank,
160+
if (
161+
self._adaptivity_output_type == "all"
162+
or self._adaptivity_output_type == "local"
163+
):
164+
self._metrics_logger.log_info(
165+
"{},{},{}".format(
166+
n,
167+
active_sims_on_this_rank,
168+
inactive_sims_on_this_rank,
169+
)
161170
)
162-
)
163171

164-
active_sims_rankwise = self._comm.gather(active_sims_on_this_rank, root=0)
165-
inactive_sims_rankwise = self._comm.gather(inactive_sims_on_this_rank, root=0)
172+
if (
173+
self._adaptivity_output_type == "global"
174+
or self._adaptivity_output_type == "all"
175+
):
176+
active_sims_rankwise = self._comm.gather(active_sims_on_this_rank, root=0)
177+
inactive_sims_rankwise = self._comm.gather(
178+
inactive_sims_on_this_rank, root=0
179+
)
166180

167-
if self._rank == 0:
168-
size = self._comm.Get_size()
181+
if self._rank == 0:
182+
size = self._comm.Get_size()
169183

170-
self._global_metrics_logger.log_info_rank_zero(
171-
"{},{},{},{},{}".format(
172-
n,
173-
sum(active_sims_rankwise) / size,
174-
sum(inactive_sims_rankwise) / size,
175-
max(active_sims_rankwise),
176-
max(inactive_sims_rankwise),
184+
self._global_metrics_logger.log_info_rank_zero(
185+
"{},{},{},{},{}".format(
186+
n,
187+
sum(active_sims_rankwise) / size,
188+
sum(inactive_sims_rankwise) / size,
189+
max(active_sims_rankwise),
190+
max(inactive_sims_rankwise),
191+
)
177192
)
178-
)
179193

180194
def _update_inactive_sims(self, micro_sims: list) -> None:
181195
"""

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