CUDA_VISIBLE_DEVICES – Masking GPUs

Src: http://acceleware.com/blog/cudavisibledevices-masking-gpus

Does your CUDA application need to target a specific GPU? If you are writing GPU enabled code, you would typically use a device query to select the desired GPUs. However, a quick and easy solution for testing is to use the environment variable CUDA_VISIBLE_DEVICES to restrict the devices that your CUDA application sees. This can be useful if you are attempting to share resources on a node or you want your GPU enabled executable to target a specific GPU.

Environment Variable Syntax	Results
CUDA_VISIBLE_DEVICES=1	Only device 1 will be seen
CUDA_VISIBLE_DEVICES=0,1	Devices 0 and 1 will be visible
CUDA_VISIBLE_DEVICES=”0,1”	Same as above, quotation marks are optional
CUDA_VISIBLE_DEVICES=0,2,3	Devices 0, 2, 3 will be visible; device 1 is masked

CUDA will enumerate the visible devices starting at zero. In the last case, devices 0, 2, 3 will appear as devices 0, 1, 2. If you change the order of the string to “2,3,0”, devices 2,3,0 will be enumerated as 0,1,2 respectively. If CUDA_VISIBLE_DEVICES is set to a device that does not exist, all devices will be masked. You can specify a mix of valid and invalid device numbers. All devices before the invalid value will be enumerated, while all devices after the invalid value will be masked.
To determine the device ID for the available hardware in your system, you can run NVIDIA’s deviceQuery executable included in the CUDA SDK. Happy programming!