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        "author": "Davis Architecture Research Group (DArchR)",
        "author_email": "jlowepower@ucdavis.edu",
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        "description": "# gem5art tasks package\n\nThis package contains two parallel task libraries for running gem5 experiments.\nhe actual gem5 experiment can be executed with the help of [Python multiprocessing support](https://docs.python.org/3/library/multiprocessing.html), [Celery](http://www.celeryproject.org/) or even without using any job manager (a job can be directly launched by calling `run()` function of gem5Run object).\nThis package implicitly depends on the gem5art run package.\n\nPlease cite the [gem5art paper](https://arch.cs.ucdavis.edu/papers/2021-3-28-gem5art) when using the gem5art packages.\nThis documentation can be found on the [gem5 website](http://www.gem5.org/documentation/gem5art/)\n\n## Use of Python Multiprocessing\n\nThis is a simple way to run gem5 jobs using Python multiprocessing library.\nYou can use the following function in your job launch script to execute gem5art run objects:\n\n```python\nrun_job_pool([a list containing all run objects you want to execute], num_parallel_jobs = [Number of parallel jobs you want to run])\n```\n\n## Use of Celery\n\nCelery server can run many gem5 tasks asynchronously.\nOnce a user creates a gem5Run object (discussed previously) while using gem5art, this object needs to be passed to a method `run_gem5_instance()` registered with Celery app, which is responsible for starting a Celery task to run gem5. The other argument needed by the `run_gem5_instance()` is the current working directory.\n\nCelery server can be started with the following command:\n\n```sh\ncelery -E -A gem5art.tasks.celery worker --autoscale=[number of workers],0\n```\n\nThis will start a server with events enabled that will accept gem5 tasks as defined in gem5art.\nIt will autoscale from 0 to desired number of workers.\n\nCelery relies on a message broker `RabbitMQ` for communication between the client and workers.\nIf not already installed, you need to install `RabbitMQ` on your system (before running celery) using:\n\n```sh\napt-get install rabbitmq-server\n```\n\n### Monitoring Celery\n\nCelery does not explicitly show the status of the runs by default.\n[flower](https://flower.readthedocs.io/en/latest/), a Python package, is a web-based tool for monitoring and administrating Celery.\n\nTo install the flower package,\n```sh\npip install flower\n```\n\nYou can monitor the celery cluster doing the following:\n\n```sh\nflower -A gem5art.tasks.celery --port=5555\n```\nThis will start a webserver on port 5555.\n\n### Removing all tasks\n\n```sh\ncelery -A gem5art.tasks.celery purge\n```\n\n### Viewing state of all jobs in celery\n\n```sh\ncelery -A gem5art.tasks.celery events\n```\n\n## Tasks API Documentation\n\n```eval_rst\nTask\n----\n\n.. automodule:: gem5art.tasks.tasks\n    :members:\n    :undoc-members:\n\n.. automodule:: gem5art.tasks.celery\n    :members:\n    :undoc-members:\n```",
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