cuda-smi-master_GPU_源码

cuda-smi ======== A simple utility to show nVidia GPU memory usage. Unlike `nvidia-smi`, it uses CUDA device IDs. For a number of reasons nVidia uses different device enumeration in `nvidia-smi` monitoring utility and in their CUDA API, making it extremely frustrating to choose vacant GPU for calculations on multi-GPU machine. This utility was made to solve this problem. Code is distributed under MIT license, except `nvml.h` header which is property of NVIDIA Corporation. CUDA 7.0 -------- With the release of CUDA 7.0, it became possible to use `nvidia-smi` device order in CUDA applications by setting environment variable `CUDA_DEVICE_ORDER=PCI_BUS_ID`. This makes this tool slightly less useful. [More information available in official docs](http://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars). Building -------- The code is compiled statically to simplify distribution over a large number of machines. Simply install more-or-less recent CUDA Toolkit and run `make`. Output example -------------- aland@NX8-1:~$ cuda-smi Device 0 [nvidia-smi 2]: GeForce GTX 680 (CC 3.0): 9 of 2047 MiB Used [PCIe ID: 0000:13:00.0] Device 1 [nvidia-smi 3]: Tesla C1060 (CC 1.3): 3 of 4095 MiB Used [PCIe ID: 0000:14:00.0] Device 2 [nvidia-smi 1]: Tesla C1060 (CC 1.3): 106 of 4095 MiB Used [PCIe ID: 0000:0d:00.0] Device 3 [nvidia-smi 0]: Tesla C2075 (CC 2.0): 13 of 6143 MiB Used [PCIe ID: 0000:0c:00.0] Device 4 [nvidia-smi 7]: Tesla C1060 (CC 1.3): 106 of 4095 MiB Used [PCIe ID: 0000:8e:00.0] Device 5 [nvidia-smi 6]: Tesla C2075 (CC 2.0): 115 of 6143 MiB Used [PCIe ID: 0000:8d:00.0] Device 6 [nvidia-smi 5]: Tesla C1060 (CC 1.3): 106 of 4095 MiB Used [PCIe ID: 0000:87:00.0] Device 7 [nvidia-smi 4]: Tesla C2075 (CC 2.0): 115 of 6143 MiB Used [PCIe ID: 0000:86:00.0]