GPU¶
The JupyterHub AMI includes NVIDIA drivers and multiple versions of CUDA to support the GPUs available on AWS and the different data science library, no extra configuration is needed.
Software | Version |
---|---|
NVIDIA Drivers |
495.29.05 |
CUDA |
11.0 |
CUDA |
11.1 |
CUDA |
11.2 |
CUDA |
11.3 |
CUDA |
11.4 |
CUDA |
11.5 |
For example, after launching AMI in a g4dn.xlarge
instance run nvidia-smi
.
Terminal
$ nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 495.29.05 Driver Version: 495.29.05 CUDA Version: 11.5 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla T4 On | 00000000:00:1E.0 Off | 0 |
| N/A 26C P8 8W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+