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Pull request overview
This PR refactors the benchmark orchestrator to run “related” ACI experiments concurrently (per benchmark run), while also reducing per-experiment CPU/RAM allocations and adjusting logging to better reflect run progress.
Changes:
- Added related-experiment parallel execution in
main.pyusingThreadPoolExecutor, plus helper functions for experiment lookup and cleanup. - Updated benchmark configuration (
benchmarks.yml) to reduce resources and introducerelated_script_idsfor grouping. - Tweaked log messages/levels to better reflect run lifecycle and container creation/deletion events.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 5 comments.
| File | Description |
|---|---|
| main.py | Runs related experiments in parallel, adds helpers (_run_container_benchmark, _get_experiment_from_id, _clear_all_container_instances), and updates logging. |
| benchmarks.yml | Lowers CPU/RAM defaults and adds related_script_ids to define parallel groups. |
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This pull request refactors the benchmark orchestration logic to support running related experiments in parallel, reduces resource allocation for all experiments, and improves logging and code organization. The main changes are grouped below:
Benchmark orchestration and parallelization:
ThreadPoolExecutor, ensuring that related experiments are executed simultaneously and only once per run. Added helper functions_run_container_benchmark,_get_experiment_from_id, and_clear_all_container_instancesto support this logic. [1] [2] [3] [4]Benchmark configuration and resource usage:
benchmarks.ymlfrom 4 CPUs and 16GB RAM to 3 CPUs and 8GB RAM, and added arelated_script_idsfield to each experiment to specify related experiments for parallel execution.Logging and code improvements:
infotodebugfor less important messages. [1] [2] [3] [4]These changes make the benchmark execution more efficient, maintainable, and resource-conscious.