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To monitor overall GPU usage with 1-second update intervals: nvidia-smi dmon To list all available NVIDIA devices, run: nvidia-smi -L The examples below are taken from this internal cluster. These are NVIDIA’s high-performance compute GPUs and provide a good deal of health and status information. Microway’s GPU Test Drive cluster, which we provide as a benchmarking service to our customers, contains a group of NVIDIA’s latest Tesla GPUs. GeForce: varying levels of support, with fewer metrics available than on the Tesla and Quadro products Querying GPU Status These include the Tesla, Quadro, and GeForce devices from Fermi and higher architecture families (Kepler, Maxwell, Pascal, Volta, etc). NVIDIA’s SMI tool supports essentially any NVIDIA GPU released since the year 2011. This should be done through NVIDIA’s graphical GPU device management panel. Instead, you need to set your computational GPUs to TCC mode. On Windows, nvidia-smi is not able to set persistence mode. Enable persistence mode on all GPUS by running:

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It is also necessary if you’ve assigned specific clock speeds or power limits to the GPUs (as those changes are lost when the NVIDIA driver is unloaded).

Persistence mode uses a few more watts per idle GPU, but prevents the fairly long delays that occur each time a GPU application is started. This is particularly useful when you have a series of short jobs running. On Linux, you can set GPUs to persistence mode to keep the NVIDIA driver loaded even when no applications are accessing the cards. | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. Here’s the default output from a recent version with four Tesla V100 GPU cards: nvidia-smi Other times, it’s just useful to make sure all the GPU cards are visible and communicating properly. Running a simple nvidia-smi query as root will initialize all the cards and create the proper devices in /dev. For example, on some systems the proper NVIDIA devices in /dev are not created at boot.

Additionally, GPU configuration options (such as ECC memory capability) may be enabled and disabled.Īs an aside, if you find that you’re having trouble getting your NVIDIA GPUs to run GPGPU code, nvidia-smi can be handy. Depending on the generation of your card, various levels of information can be gathered.

The tool is NVIDIA’s System Management Interface ( nvidia-smi).

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Thankfully, NVIDIA’s latest hardware and software tools have made good improvements in this respect. If you don’t know where to look, it can even be difficult to determine the type and capabilities of the GPUs in a system. In contrast, keeping tabs on the health and status of GPUs has historically been more difficult.

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Most users know how to check the status of their CPUs, see how much system memory is free, or find out how much disk space is free.