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This makes this tool slightly less useful.\n\n[More information available in official docs](http://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars).\n\nBuilding\n--------\n\nThe code is compiled statically to simplify distribution over a large number of machines.\n\nSimply install more-or-less recent CUDA Toolkit and run `make`.\n\nOutput example\n--------------\n    aland@NX8-1:~$ cuda-smi \n    Device  0 [nvidia-smi  2]:      GeForce GTX 680 (CC 3.0):     9 of  2047 MiB Used [PCIe ID: 0000:13:00.0]\n    Device  1 [nvidia-smi  3]:          Tesla C1060 (CC 1.3):     3 of  4095 MiB Used [PCIe ID: 0000:14:00.0]\n    Device  2 [nvidia-smi  1]:          Tesla C1060 (CC 1.3):   106 of  4095 MiB Used [PCIe ID: 0000:0d:00.0]\n    Device  3 [nvidia-smi  0]:          Tesla C2075 (CC 2.0):    13 of  6143 MiB Used [PCIe ID: 0000:0c:00.0]\n    Device  4 [nvidia-smi  7]:          Tesla C1060 (CC 1.3):   106 of  4095 MiB Used [PCIe ID: 0000:8e:00.0]\n    Device  5 [nvidia-smi  6]:          Tesla C2075 (CC 2.0):   115 of  6143 MiB Used [PCIe ID: 0000:8d:00.0]\n    Device  6 [nvidia-smi  5]:          Tesla C1060 (CC 1.3):   106 of  4095 MiB Used [PCIe ID: 0000:87:00.0]\n    Device  7 [nvidia-smi  4]:          Tesla C2075 (CC 2.0):   115 of  6143 MiB Used [PCIe ID: 0000:86:00.0]\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fal42and%2Fcuda-smi","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fal42and%2Fcuda-smi","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fal42and%2Fcuda-smi/lists"}