Scheduler is a tool for effective GPU utilization. The typical usage is e.g. training many machine learning models on multiple GPUs. Using the scheduler allows you to easily schedule more tasks than your total number of GPUs.
Scheduler uses the file gpu_scheduler_info which is stored in /tmp/ and contains the global GPUs state. This file is automatically created on the first start and, by default, is initialized for four GPU (it can be change with --init option). When a particular task is assigned to some GPU, a global variable GPU is set to cuda[id of assigned GPU] and this GPU is blocked until the task finishes.
/path/to/scheduler.py "train.py foo --bar 5" --forced_gpu 2 --verbose
In a above example the task train.py foo --bar 5 will be started as soon as GPU 2 is free.
usage: schedule [-h] [-gc GPU_COUNT] [-i INIT [INIT ...]] [-v] [-o [OUT]]
[-e [ERR]] [-pg PREFERED_GPU] [-fg FORCED_GPU] [-s]
[-rg RELEASE_GPU [RELEASE_GPU ...]]
[task]
positional arguments:
task The quoted task with arguments which will be started
on free GPUs as soon as possible.
optional arguments:
-h, --help show this help message and exit
-gc GPU_COUNT, --gpu_count GPU_COUNT
The count of required GPUs for specified task.
-i INIT [INIT ...], --init INIT [INIT ...]
Initializes gpu info file. List of numbers is
expected, where first number is total count of GPUs
and the rest of the numbers denotes unavailable GPUs.
e.g -i 5 3 4 means that total count of GPUs is 5 and
GPU 3 and 4 are currently unavailable.
-v, --verbose Prints info about the process, when the task is
completed.
-o [OUT], --out [OUT]
The name of the file, which will be used to store
stdout. The default file is sys.stdout.
-e [ERR], --err [ERR]
The name of the file, which will be used to store
stderr. The default file is sys.stderr.
-pg PREFERED_GPU, --prefered_gpu PREFERED_GPU
If possible, prefered GPU is assigned to the task,
otherwise is assigned random free GPU.
-fg FORCED_GPU, --forced_gpu FORCED_GPU
Wait until specified GPU is free.
-s, --status Show info about GPU usage - user/GPU/taskPID/start
-rg RELEASE_GPU [RELEASE_GPU ...], --release_gpu RELEASE_GPU [RELEASE_GPU ...]
Releases GPUs according their indices. e.g -rg 0 2
will release GPU 0 and 2.
You are welcome to participate in development of this project.
Scheduler is distributed under the MIT License.
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