Difference between revisions of "Nvidia-smi"
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↑ https://apple.stackexchange.com/a/287627
Tags: Mobile web edit, Mobile edit |
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* <code>[[gpustat]]</code> | * <code>[[gpustat]]</code> | ||
* <code>[[glances]]</code> monitoring tool | * <code>[[glances]]</code> monitoring tool | ||
+ | * [[nvcc --version]] | ||
== See also == | == See also == |
Revision as of 13:40, 27 May 2024
This article is a Draft. Help us to complete it.
nvidia-smi nvidia-smi -l 1 watch -n 1 nvidia-smi
nvidia-smi
Sat Apr 11 11:31:22 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 410.104 Driver Version: 410.104 CUDA Version: 10.0 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | |===============================+======================+======================| | 0 Tesla T4 On | 00000000:21:01.0 Off | 0 | | N/A 35C P0 26W / 70W | 2414MiB / 15079MiB | 0% Default | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: GPU Memory | | GPU PID Type Process name Usage | |=============================================================================| | 0 20148 C /usr/bin/python 2404MiB | +-----------------------------------------------------------------------------+
macOS
In macOS there is no nvidia-smi command that comes with nvidia drivers. However, you could check this open-source alternative : https://github.com/phvu/cuda-smi
Edit in 2020 : As an alternative to nvidia-smi is Activity Monitor. Search on spotlight (cmd + space) and type Activity Monitor. When the program opens press cmd + 4. This will show you the active usage of GPU(s) on your system. I think this feature comes with High Sierra 10.13 prior to that there is no option for gpu history. [1]
Related terms
gpustat
glances
monitoring tool- nvcc --version
See also
- Nvidia, GPU,
nvidia-smi
, CUDA, Nvidia Drive, Tegra, EVGA Corporation, A10, A100, H100, T4, L4,gpustat
, Nvidia Xavier, NVML, TOPS, Nvidia broadcast, Mellanox, Jensen Huang, NVIDIA driver, Nvidia RTX, Tensor Cores, Nvidia DGX, Nvidia Omniverse Cloud, Drive Thor, Ada, Hopper
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