gpus_monitor/README.md

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# GPUs Monitor
`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
that has been launched.
You will also receive an email if a compute process died (with EXIT_STATUS = 0 or not).
### Kind of mail gpus_monitor is going to send you :
1. New training detected :
>> From: <gpusstatus@mydomain.com>
>> Subject : 1 processes running on <MACHINE_NAME> (LOCAL_IP_OF_THE_MACHINE)
>>
>> New events (triggered on the 08/11/2020 11:45:52):
>>
>> ---------------------------------------------------------------------------------------------------------------
>> 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
>> His owner (<owner_of_the_process>) has executed the following command :
>> python3 test_torch.py
>> From :
>> <absolute_path_to_the_script_of_the_new_launched_process>
>>
>> CPU Status (currently):
>> For this process : 19/40 logic cores (47.5%)
>>
>> GPU Status (currently):
>> - Used memory (for this process): 879 / 7979.1875 MiB (11.02 % used)
>> - Used memory (for all processes running on this GPU) 7935.3125 / 7979.1875 MiB (99.45 % used)
>> - Temperature : 83 Celsius
>> - Driver version : 435.21
>> ---------------------------------------------------------------------------------------------------------------
>>
>>
>>
>> This message has been automatically send by a robot. Please don't answer to this mail
>> 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
2. Training died (either finished well or not)
>> From: <gpusstatus@mydomain.com>
>> Subject : 1 processes running on <MACHINE_NAME> (LOCAL_IP_OF_THE_MACHINE)
>>
>> New events (triggered on the 08/11/2020 11:47:29):
>>
>> ---------------------------------------------------------------------------------------------------------------
>> The process (PID : 12350) launched by araison since 08/11/2020 11:43:48 has ended.
>> His owner araison had executed the following command :
>> python3 test_torch.py
>> From :
>> <absolute_path_to_the_script_of_the_died_process>
>>
>> The process took 0:03:41 to finish.
>> --------------------------------------------------------------------------------------------------------------
>>
>> This message has been automatically send by a robot. Please don't answer to this mail
>> 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
## Instructions to use gpus_monitor :
1. Cloning this repository :
`git clone https://github.com/araison12/gpus_monitor.git`
2. Installing dependencies :
`pip3 install -r gpus_monitor/requirements.txt`
or
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`python3 gpus_monitor/setup.py install --user`
3. Add peoples mail to the list of the `persons_to_inform.yaml` file :
Example:
```yaml
list:
- adrien.raison@univ-poitiers.fr
- other_person_to_inform@hisdomain.com
```
Note : You can hot-add/remove mails in this file without the need of killing the scanning process !
4. Add SMTP Server parameters (server adress, credentials, port number, etc..)
You can manage these stuff in the `gpus_monitor/src/gpus_monitor/config.py` file :
To adjust these varibales you have to edit the `gpus_monitor/src/gpus_monitor/config.py` file.
```bash
cd gpus_monitor/src/gpus_monitor/
vim config.py
```
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For privacy purposes, login of my dedicated SMTP account are stored in a machine in 2 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 each `gpus_monitor` instance listening several machine (max 100 mails/24h) , feel free to send me an email if you are interested in !
Otherwise, fill in with your own SMTP server configuration.
```python
USER = os.environ.get(
"GPUSMONITOR_MAIL_USER"
)
PASSWORD = os.environ.get(
"GPUSMONITOR_MAIL_PASSWORD"
)
PORT = 465
SMTP_SERVER = "smtp.gmail.com"
```
See https://askubuntu.com/a/58828 to handle efficiently (permanent adding) environment variables.
5. Adjust the scanning rate of `gpus_monitor` and the processes age that he has to take in account.
The `WAITING_TIME` variable adjusts the scan timing rate of gpus_monitor.
```python
WAITING_TIME = 0.5 # min
```
The `PROCESS_AGE` variable adjusts the processes age that gpus_monitor has to take in account.
```python
PROCESS_AGE = 2 # min (gpus_monitor only consider >=2min aged processes)
```
6. Executing `gpus_monitor` when machine starts up.
```bash
crontab -e
```
Add the following line to the brandnew opened file :
```bash
@reboot python3 /path/to/gpu_monitor/src/gpus_monitor/main.py
```
## Ideas to enhanced the project :
- Log system (owner, total calculation time by user)
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- Manage cases (subject): processes finished well or not (Send Traceback)
- Centralized system that scan every machine on a given IP adresses range.
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- Better errors management (SMTP connection failed, no Cuda compatible GPU on the machine,..)
- Documenting the project
- Rewrite it in oriented object fashion
If you have any ideas to improve this project, don't hesitate to make a merge request ! :)
## To test `gpus_monitors` by your own:
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I've implemented the tiny non linear XOR problem in pyTorch.
You can test `gpus_monitor` by your own while running :
```bash
python3 gpus_monitor/test_torch.py
```