Open peihsunhsieh opened 2 months ago
Describe the bug
Version: mesa 2.3.4
I encountered an issue where the model runs much slower when using batch_run compared to running the same model manually.
When running the model manually for 100 steps, it completed in just 2 minutes:
test_model = Societies_G2_LTX(N=1000,g1_learning_type='PB',g2_learning_type='CB', group2_prop=0.1, g1_init='r') for _ in range(100): test_model.step()
However, when I used batch_runwith the same parameters, the model kept running for over 10 minutes, even for only ten steps:
batch_run
params = {'N':1000, 'g1_learning_type':'PB','g2_learning_type':'CB', 'group2_prop':0.45,'g1_init':'r'} Societies_G2_LTX_test = mesa.batch_run( Societies_G2_LTX, parameters=params, iterations=1, max_steps=10, number_processes=1, data_collection_period=1, display_progress=True, )
Is there any known issue when using batch_run, or am I missing something in the configuration that could be causing this significant slowdown? Is it related to the issue in #2135 ?
Thanks for reporting this potential issue. Could you share the full model? Then I will try to reproduce it.
Describe the bug
Version: mesa 2.3.4
I encountered an issue where the model runs much slower when using batch_run compared to running the same model manually.
When running the model manually for 100 steps, it completed in just 2 minutes:
However, when I used
batch_run
with the same parameters, the model kept running for over 10 minutes, even for only ten steps:Is there any known issue when using batch_run, or am I missing something in the configuration that could be causing this significant slowdown? Is it related to the issue in #2135 ?