gpumutex
This library can be injected into existing CUDA programs with GPUs, such that no process also run under libgpumutex can interfere with another.
This is accomplished through relatively interesting means. See the design writeup: https://apaz.dev/blog/LD_PRELOAD.html
Linux only (glibc; uses dl_iterate_phdr/ELF parsing internally).
Installing with pip
pip install gpumutex
GPUMUTEX_VISIBLE_DEVICES=0,1,2,3 gpumutex-run -- python train.py
# or, equivalently:
gpumutex-run --visible-devices 0,1,2,3 -- python train.py
import gpumutex
gpumutex.run(["python", "train.py"], visible_devices="0,1,2,3", check=True)
gpumutex.system("python train.py", visible_devices=[0, 1, 2, 3])
Using Standalone
# Compile
cc -shared -fPIC -fvisibility=hidden -o libgpumutex.so gpumutex/libgpumutex.c -ldl -lpthread
Then to run a program under it:
LD_PRELOAD=./libgpumutex.so GPUMUTEX_VISIBLE_DEVICES=... program program_args
Configuration
Both usages below are configured the same way as the raw interposer, via
environment variables. gpumutex-run and gpumutex.run()/gpumutex.system()
also accept these directly as CLI flags / keyword arguments, which set the
variable in the child's environment only, without touching your own:
| Variable | CLI flag | Python kwarg | Description | Default |
|---|---|---|---|---|
GPUMUTEX_VISIBLE_DEVICES |
--visible-devices |
visible_devices |
Comma-separated device indices to manage (e.g. "0,2,3"), or an iterable of indices in Python. Required; without it, the preload is inert. |
none (required) |
GPUMUTEX_NUM_DEVICES |
--num-devices |
num_devices |
How many of those devices one process tree needs at once. | 1 |
GPUMUTEX_LOCK_DIR |
--lock-dir |
lock_dir |
Where lockfiles and the wait queue live. | /tmp/libgpumutex |
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