CGH0S7
85afe00fc5
- Implement multiprocessing-based parallel plotting - Add parallel_plot_helper.py for concurrent plot task execution - Use matplotlib 'Agg' backend for multiprocessing safety - Set OMP_NUM_THREADS=1 to prevent BLAS thread explosion - Use subprocess for binary data plots to avoid thread conflicts - Add fork bomb protection in main program This merge only includes plotting improvements and excludes MPI communication changes to preserve existing optimizations. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
30 lines
810 B
Python
30 lines
810 B
Python
import multiprocessing
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def run_plot_task(task):
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"""Execute a single plotting task.
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Parameters
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----------
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task : tuple
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A tuple of (function, args_tuple) where function is a callable
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plotting function and args_tuple contains its arguments.
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"""
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func, args = task
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return func(*args)
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def run_plot_tasks_parallel(plot_tasks):
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"""Execute a list of independent plotting tasks in parallel.
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Uses the 'fork' context to create worker processes so that the main
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script is NOT re-imported/re-executed in child processes.
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Parameters
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----------
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plot_tasks : list of tuples
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Each element is (function, args_tuple).
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"""
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ctx = multiprocessing.get_context('fork')
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with ctx.Pool() as pool:
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pool.map(run_plot_task, plot_tasks)
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