Testing by your own the project in README
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README.md
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# GPUs Monitor
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`gpus_monitor` is a Python GPUs activities monitoring tool designed to report by email new and recently died compute processes over the machine where it has been run on.
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Basically, when you have just run a new stable training on the machine where `gpus_monitor` listen to, you will received in a few seconds an email notification. This email will contains several informations about the process you've launched.
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You received also an email if a compute process died (with EXIT_STATUS = 0 or not).
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### Kind of mail gpus_monitor is going to send you :
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1. New training detected :
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>> From: <gpusstatus@mydomain.com>
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>> Subject : 1 processes running on <MACHINE_NAME> (LOCAL_IP_OF_THE_MACHINE)
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>>
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>> New events (triggered on the 08/11/2020 11:45:52):
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>>
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>> ---------------------------------------------------------------------------------------------------------------
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>> A new process (PID : 12350) has been launched on GPU 0 (Quadro RTX 4000) by <owner_of_the_process> since 08/11/2020 11:43:48
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>> His owner (<owner_of_the_process>) has executed the following command :
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>> python3 test_torch.py
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>> From :
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>> <absolute_path_to_the_script_of_the_new_launched_process>
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>>
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>> CPU Status (currently):
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>> For this process : 19/40 logic cores (47.5%)
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>>
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>> GPU Status (currently):
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>> - Used memory (for this process): 879 / 7979.1875 MiB (11.02 % used)
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>> - Used memory (for all processes running on this GPU) 7935.3125 / 7979.1875 MiB (99.45 % used)
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>> - Temperature : 83 Celsius
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>> - Driver version : 435.21
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>> ---------------------------------------------------------------------------------------------------------------
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>>
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>>
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>>
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>> This message has been automatically send by a robot. Please don't answer to this mail
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>> Please, feel free to open a merge request on github.com/araison12/gpus_monitor if you have encountered a bug or to share your ideas to improve this tool
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2. Training died (either finished well or not)
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>> From: <gpusstatus@mydomain.com>
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>> Subject : 1 processes running on <MACHINE_NAME> (LOCAL_IP_OF_THE_MACHINE)
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>>
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>> New events (triggered on the 08/11/2020 11:47:29):
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>>
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>> ---------------------------------------------------------------------------------------------------------------
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>> The process (PID : 12350) launched by araison since 08/11/2020 11:43:48 has ended.
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>> His owner araison had executed the following command :
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>> python3 test_torch.py
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>> From :
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>> <absolute_path_to_the_script_of_the_died_process>
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>>
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>> The process took 0:03:41 to finish.
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>> --------------------------------------------------------------------------------------------------------------
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>>
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>> This message has been automatically send by a robot. Please don't answer to this mail
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>> Please, feel free to open a merge request on github.com/araison12/gpus_monitor if you have encountered a bug or to share your ideas to improve this tool
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## Instructions to use gpus_monitor :
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1. Cloning this repository :
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`git clone https://github.com/araison12/gpus_monitor.git`
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2. Installing dependencies :
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`pip3 install -r gpus_monitor/requirements.txt`
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or
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`python3 setup.py install --user`
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3. Add peoples mail to the list of the `persons_to_inform.yaml` file :
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Example:
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```yaml
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list:
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- adrien.raison@univ-poitiers.fr
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- other_person_to_inform@hisdomain.com
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```
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Note : You can hot-add/remove mails in this file without the need of killing the scanning process !
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4. Add SMTP Server parameters (server adress, credentials, port number, etc..)
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You can manage these stuff in the `gpus_monitor/src/gpus_monitor/config.py` file :
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To adjust these varibales you have to edit the `gpus_monitor/src/gpus_monitor/config.py` file.
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```bash
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cd gpus_monitor/src/gpus_monitor/
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vim config.py
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```
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For privacy purposes, login of my dedicated SMTP account are stored in 2 machine environment variables. I've set up a brandnew Gmail account for my `gpus_monitor` instance. I can share with you my credentials in order to use a single SMTP account for `gpus_monitor` instance on several machines, feel free to send me an email !
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Otherwise, fill in with your own SMTP server configuration.
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```python
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USER = os.environ.get(
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"GPUSMONITOR_MAIL_USER"
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)
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PASSWORD = os.environ.get(
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"GPUSMONITOR_MAIL_PASSWORD"
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)
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PORT = 465
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SMTP_SERVER = "smtp.gmail.com"
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```
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See https://askubuntu.com/a/58828 to handle efficiently (permanent adding) environment variables.
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5. Adjust the scanning rate of `gpus_monitor` and the processes age that he has to take in account.
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The `WAITING_TIME` variable adjusts the scan timing rate of gpus_monitor.
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```python
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WAITING_TIME = 0.5 # min
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```
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The `PROCESS_AGE` variable adjusts the processes age that gpus_monitor has to take in account.
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```python
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PROCESS_AGE = 2 # min (gpus_monitor only consider >=2min aged processes)
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```
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6. Executing `gpus_monitor` when machine starts up.
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```bash
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crontab -e
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```
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Add the following line to the brandnew opened file :
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```bash
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@reboot python3 /path/to/gpu_monitor/src/gpus_monitor/main.py
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```
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# Ideas to enhanced the project :
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- Log system (owner, total calculation time by user)
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- Manage cases in email sending (subject): processes finished well or not (Send Traceback)
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- Centralized system that scan every machine on a given IP adresses range.
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- Better errors management (SMTP connection failed, no Cuda GPU on the machine,..)
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- Documenting the project
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- Rewrite it in oriented object fashion
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If you have any ideas to improve this project, don't hesitate to make a merge request ! :)
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# To test `gpus_monitors` by your own:
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I've implemented a the tiny non linear XOR problem in pyTorch.
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You can test `gpus_monitor` by your own while running :
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```bash
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python3 gpus_monitor/test_torch.py
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```
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