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FAQ

Multi-GPU machines

To distribute multiple HALMD processes among CUDA devices in a single machine, the CUDA devices have to be locked exclusively by the respective process. HALMD will then choose the first available CUDA device, or an available device in the subset given by the --device option.

nvidia-smi tool

If your NVIDIA driver version comes with the nvidia-smi tool, set all CUDA devices to compute exclusive mode to restrict use to one process per device:

sudo nvidia-smi --gpu=0 --compute-mode-rules=1
sudo nvidia-smi --gpu=1 --compute-mode-rules=1

Warning

Compute exclusive mode seems to work reliably only with NVIDIA Tesla devices. Although NVIDIA GeForce cards may be set to compute exclusive mode as well, doing so might occasionally cause a system crash.

nvlock tool

If your NVIDIA driver version does not support the nvidia-smi tool, or if you wish not to set the devices to compute exclusive mode, the nvlock tool may be used to exclusively assign a GPU to each process:

nvlock halmd [...]

You may also directly use the preload library:

LD_PRELOAD=libnvlock.so halmd [...]

nvlock is available at

git://git.colberg.org/nvcuda-tools

or using the “dumb” HTTP protocol

http://git.colberg.org/nvcuda-tools

and is compiled with

cmake .
make