Update

1. My fork's name was n_gpu, but I find that if we want to uninstall it , we should use pip uninstall gpustat, so the n_gpu is missing. So switch back to gpustat.

2. For better experience for Chinese users, I mainly focus on https://gitee.com/llwwff/gpustat instead of github' s repo

---

n_gpu: number of available gpu / new gpu command, do not use the ugly nvidia-smi anymore.

Install

python -m pip install git+https://github.com/sisrfeng/n_gpu

• forked from wookayin/gpustat (v0.6) (The original repo' s version is higher now, but I'm quite satisfied with this version.)

• The code is not complex: gpu_stats in main.py call print_formatted(sys.stdout, **kwargs) in core.py.
  I just modified the two files above.

Automatically Find the GPUs with Most MEM Available

nvidia-smi then set CUDA_VISIBLE_DEVICES manually?

I have not typed these two for a long time.

source alias.zsh in your zshrc file, then type p in zsh instead of python3

See ./find_gpus.py and alias.zsh before you use them!

Original README.md

gpustat

no AMD support as of now

Usage

$ gpustat

Options:

• --color : Force colored output (even when stdout is not a tty)
• --no-color : Suppress colored output
• -u, --show-user : Display username of the process owner
• -c, --show-cmd : Display the process name
• -f, --show-full-cmd : Display full command and cpu stats of running process
• -p, --show-pid : Display PID of the process
• -F, --show-fan : Display GPU fan speed
• -e, --show-codec : Display encoder and/or decoder utilization
• -P, --show-power : Display GPU power usage and/or limit (draw or draw,limit)
• -a, --show-all : Display all gpu properties above
• --watch, -i, --interval : Run in watch mode (equivalent to watch gpustat) if given. Denotes interval between updates. (#41)
• --json : JSON Output (Experimental, #10)

Tips

• To periodically watch, try gpustat --watch or gpustat -i (#41).
  • For older versions, one may use watch --color -n1.0 gpustat --color.
• Running nvidia-smi daemon (root privilege required) will make the query much faster and use less CPU (#54).
• The GPU ID (index) shown by gpustat (and nvidia-smi) is PCI BUS ID, while CUDA differently assigns the fastest GPU with the lowest ID by default. Therefore, in order to make CUDA and gpustat use same GPU index, configure the CUDA_DEVICE_ORDER environment variable to PCI_BUS_ID (before setting CUDA_VISIBLE_DEVICES for your CUDA program): export CUDA_DEVICE_ORDER=PCI_BUS_ID.

Starting from v1.0, gpustat will support only Python 3.4+.

Default display

[0] GeForce GTX Titan X | 77'C, 96 % | 11848 / 12287 MB | python/52046(11821M)

• [0]: GPUindex (starts from 0) as PCI_BUS_ID
• GeForce GTX Titan X: GPU name
• 77'C: Temperature
• 96 %: Utilization
• 11848 / 12287 MB: GPU Memory Usage
• python/...: Running processes on GPU (and their memory usage)

License

MIT License