I am using the Salabim package in python to simulate some queueing theory. Salabim (documentation) is based on SimPy but with many extensions and additional features. Most of my problems are solved in a few minutes with minimal memory requirements.
However, I want to extend the model and noted that the simulation captures about 32GB after 1 hour of simulation of a simple M/M/1 queueing problem. I expect this is due to some internal monitors capturing statistical data. I have tried to deactivate most of them but till now without success.
- What statement am I missing?
- What can I change to minimize memory requirements?
Please note that I switch of monitoring for each class with the following code:
def setup(self):
self.mode.monitor(False)
self.status.monitor(False) # added 17 nov, salabim team tip
# passivate/activate method
# https://www.salabim.org/manual/Modelling.html#a-bank-example
import salabim as sim
class CarGenerator(sim.Component):
def setup(self):
self.mode.monitor(False)
self.status.monitor(False) # added 17 nov, salabim team tip
def process(self):
while True:
Car()
self.hold(iat_distr.sample())
class Car(sim.Component):
def setup(self):
self.mode.monitor(False)
self.status.monitor(False) # added 17 nov, salabim team tip
def process(self):
self.enter(waitingline)
for ChargingStation in ChargingStations:
if ChargingStation.ispassive():
ChargingStation.activate()
break # activate at most one charging station
self.passivate()
class ChargingStation(sim.Component):
def setup(self):
self.mode.monitor(False)
self.status.monitor(False) # added 17 nov, salabim team tip
def process(self):
while True:
while len(waitingline) == 0:
self.passivate()
self.car = waitingline.pop()
self.hold(srv_distr.sample())
self.car.activate()
N_STATION = 1
iat_distr = sim.Exponential(60 / 40)
srv_distr = sim.Exponential(60 / 50)
# https://www.salabim.org/manual/Reference.html#environment
app = sim.App(
trace=False, # defines whether to trace or not
random_seed="*", # if “*”, a purely random value (based on the current time)
time_unit="minutes", # defines the time unit used in the simulation
name="Charging Station", # name of the simulation
do_reset=True, # defines whether to reset the simulation when the run method is called
yieldless=True, # defines whether the simulation is yieldless or not
)
# Instantiate and activate the client generator
CarGenerator(name="Electric Cars Generator")
# Create Queue and set monitor to stats_only
waitingline = sim.Queue(name="Waiting Cars", monitor=False)
waitingline.length_of_stay.monitor(value=True)
waitingline.length_of_stay.reset_monitors(stats_only=True)
# Instantiate the servers, list comprehension but only 1 server
ChargingStations = [ChargingStation() for _ in range(N_STATION)]
# Execute Simulation
app.run(till=sim.inf)
# Print statistics
waitingline.length_of_stay.print_statistics()
I am running 'CPython' with python version 3.9.18 and SALABIM version 23.3.11.1 on Ubuntu 22.04 on a Windows Subsystem for Linux (but same happens on a pure Ubuntu 22.04 system)
WSL version: 1.2.5.0
Kernel version: 5.15.90.1
WSLg version: 1.0.51
MSRDC version: 1.2.3770
Direct3D version: 1.608.2-61064218
DXCore version: 10.0.25131.1002-220531-1700.rs-onecore-base2-hyp
Windows version: 10.0.19045.3693
The following ENV.yml file can be used to recreate the conda environment or check package versions.
name: mem_salabim
channels:
- conda-forge
- nodefaults
dependencies:
- _libgcc_mutex=0.1=conda_forge
- _openmp_mutex=4.5=2_gnu
- anyio=4.0.0=pyhd8ed1ab_0
- argon2-cffi=23.1.0=pyhd8ed1ab_0
- argon2-cffi-bindings=21.2.0=py39hd1e30aa_4
- arrow=1.3.0=pyhd8ed1ab_0
- asttokens=2.4.1=pyhd8ed1ab_0
- async-lru=2.0.4=pyhd8ed1ab_0
- attrs=23.1.0=pyh71513ae_1
- babel=2.13.1=pyhd8ed1ab_0
- backports=1.0=pyhd8ed1ab_3
- backports.functools_lru_cache=1.6.5=pyhd8ed1ab_0
- beautifulsoup4=4.12.2=pyha770c72_0
- bleach=6.1.0=pyhd8ed1ab_0
- brotli-python=1.1.0=py39h3d6467e_1
- bzip2=1.0.8=hd590300_5
- ca-certificates=2023.7.22=hbcca054_0
- cached-property=1.5.2=hd8ed1ab_1
- cached_property=1.5.2=pyha770c72_1
- certifi=2023.7.22=pyhd8ed1ab_0
- cffi=1.16.0=py39h7a31438_0
- charset-normalizer=3.3.2=pyhd8ed1ab_0
- comm=0.1.4=pyhd8ed1ab_0
- debugpy=1.8.0=py39h3d6467e_1
- decorator=5.1.1=pyhd8ed1ab_0
- defusedxml=0.7.1=pyhd8ed1ab_0
- entrypoints=0.4=pyhd8ed1ab_0
- exceptiongroup=1.1.3=pyhd8ed1ab_0
- executing=2.0.1=pyhd8ed1ab_0
- fqdn=1.5.1=pyhd8ed1ab_0
- greenlet=3.0.1=py39h3d6467e_0
- idna=3.4=pyhd8ed1ab_0
- importlib-metadata=6.8.0=pyha770c72_0
- importlib_metadata=6.8.0=hd8ed1ab_0
- importlib_resources=6.1.1=pyhd8ed1ab_0
- ipykernel=6.26.0=pyhf8b6a83_0
- ipython=8.17.2=pyh41d4057_0
- isoduration=20.11.0=pyhd8ed1ab_0
- jedi=0.19.1=pyhd8ed1ab_0
- jinja2=3.1.2=pyhd8ed1ab_1
- json5=0.9.14=pyhd8ed1ab_0
- jsonpointer=2.4=py39hf3d152e_3
- jsonschema=4.19.2=pyhd8ed1ab_0
- jsonschema-specifications=2023.7.1=pyhd8ed1ab_0
- jsonschema-with-format-nongpl=4.19.2=pyhd8ed1ab_0
- jupyter-lsp=2.2.0=pyhd8ed1ab_0
- jupyter_client=8.6.0=pyhd8ed1ab_0
- jupyter_core=5.5.0=py39hf3d152e_0
- jupyter_events=0.9.0=pyhd8ed1ab_0
- jupyter_server=2.10.0=pyhd8ed1ab_0
- jupyter_server_terminals=0.4.4=pyhd8ed1ab_1
- jupyterlab=4.0.8=pyhd8ed1ab_0
- jupyterlab_pygments=0.2.2=pyhd8ed1ab_0
- jupyterlab_server=2.25.1=pyhd8ed1ab_0
- ld_impl_linux-64=2.40=h41732ed_0
- libffi=3.4.2=h7f98852_5
- libgcc-ng=13.2.0=h807b86a_3
- libgomp=13.2.0=h807b86a_3
- libnsl=2.0.1=hd590300_0
- libsodium=1.0.18=h36c2ea0_1
- libsqlite=3.44.0=h2797004_0
- libstdcxx-ng=13.2.0=h7e041cc_3
- libuuid=2.38.1=h0b41bf4_0
- libzlib=1.2.13=hd590300_5
- markupsafe=2.1.3=py39hd1e30aa_1
- matplotlib-inline=0.1.6=pyhd8ed1ab_0
- mistune=3.0.2=pyhd8ed1ab_0
- nbclient=0.8.0=pyhd8ed1ab_0
- nbconvert-core=7.11.0=pyhd8ed1ab_0
- nbformat=5.9.2=pyhd8ed1ab_0
- ncurses=6.4=h59595ed_2
- nest-asyncio=1.5.8=pyhd8ed1ab_0
- notebook=7.0.6=pyhd8ed1ab_0
- notebook-shim=0.2.3=pyhd8ed1ab_0
- openssl=3.1.4=hd590300_0
- overrides=7.4.0=pyhd8ed1ab_0
- packaging=23.2=pyhd8ed1ab_0
- pandocfilters=1.5.0=pyhd8ed1ab_0
- parso=0.8.3=pyhd8ed1ab_0
- pexpect=4.8.0=pyh1a96a4e_2
- pickleshare=0.7.5=py_1003
- pip=23.3.1=pyhd8ed1ab_0
- pkgutil-resolve-name=1.3.10=pyhd8ed1ab_1
- platformdirs=4.0.0=pyhd8ed1ab_0
- prometheus_client=0.18.0=pyhd8ed1ab_1
- prompt-toolkit=3.0.41=pyha770c72_0
- prompt_toolkit=3.0.41=hd8ed1ab_0
- psutil=5.9.5=py39hd1e30aa_1
- ptyprocess=0.7.0=pyhd3deb0d_0
- pure_eval=0.2.2=pyhd8ed1ab_0
- pycparser=2.21=pyhd8ed1ab_0
- pygments=2.16.1=pyhd8ed1ab_0
- pysocks=1.7.1=pyha2e5f31_6
- python=3.9.18=h0755675_0_cpython
- python-dateutil=2.8.2=pyhd8ed1ab_0
- python-fastjsonschema=2.18.1=pyhd8ed1ab_0
- python-json-logger=2.0.7=pyhd8ed1ab_0
- python_abi=3.9=4_cp39
- pytz=2023.3.post1=pyhd8ed1ab_0
- pyyaml=6.0.1=py39hd1e30aa_1
- pyzmq=25.1.1=py39h8c080ef_2
- readline=8.2=h8228510_1
- referencing=0.30.2=pyhd8ed1ab_0
- requests=2.31.0=pyhd8ed1ab_0
- rfc3339-validator=0.1.4=pyhd8ed1ab_0
- rfc3986-validator=0.1.1=pyh9f0ad1d_0
- rpds-py=0.12.0=py39h9fdd4d6_0
- send2trash=1.8.2=pyh41d4057_0
- setuptools=68.2.2=pyhd8ed1ab_0
- six=1.16.0=pyh6c4a22f_0
- sniffio=1.3.0=pyhd8ed1ab_0
- soupsieve=2.5=pyhd8ed1ab_1
- stack_data=0.6.2=pyhd8ed1ab_0
- terminado=0.18.0=pyh0d859eb_0
- tinycss2=1.2.1=pyhd8ed1ab_0
- tk=8.6.13=noxft_h4845f30_101
- tomli=2.0.1=pyhd8ed1ab_0
- tornado=6.3.3=py39hd1e30aa_1
- traitlets=5.13.0=pyhd8ed1ab_0
- types-python-dateutil=2.8.19.14=pyhd8ed1ab_0
- typing-extensions=4.8.0=hd8ed1ab_0
- typing_extensions=4.8.0=pyha770c72_0
- typing_utils=0.1.0=pyhd8ed1ab_0
- tzdata=2023c=h71feb2d_0
- uri-template=1.3.0=pyhd8ed1ab_0
- urllib3=2.1.0=pyhd8ed1ab_0
- wcwidth=0.2.10=pyhd8ed1ab_0
- webcolors=1.13=pyhd8ed1ab_0
- webencodings=0.5.1=pyhd8ed1ab_2
- websocket-client=1.6.4=pyhd8ed1ab_0
- wheel=0.41.3=pyhd8ed1ab_0
- xz=5.2.6=h166bdaf_0
- yaml=0.2.5=h7f98852_2
- zeromq=4.3.5=h59595ed_0
- zipp=3.17.0=pyhd8ed1ab_0
- pip:
- salabim==23.3.11.1
prefix: /home/floris/miniforge3/envs/jads_salabim
On 28 November 2023 a new version (23.3.12) of Salabim package has been released which solves this issue and doesn't need the patch anymore as suggested.