Try to use nvidia geforce rtx 2080 ti do some computing

Accelerated Computing CUDA CUDA Setup and Installation
1

Hi, everyone,

I am trying to build a small station with nvidia geforce rtx 2080 ti which can be used to perform AI computing related study and practice.
I installed the CUDA driver. However, I have below problems:

  1. I cannot use “nvidia-smi” to see the GPU info which includes the number of CUDA cores, etc. Below is what I got after running this command.
    ±----------------------------------------------------------------------------+
    | NVIDIA-SMI 515.43.04 Driver Version: 515.43.04 CUDA Version: 11.7 |
    |-------------------------------±---------------------±---------------------+
    | 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 NVIDIA GeForce … On | 00000000:3B:00.0 Off | N/A |
    | 29% 32C P8 16W / 250W | 3MiB / 11264MiB | 0% Default |
    | | | N/A |
    ±------------------------------±---------------------±---------------------+
    | 1 NVIDIA GeForce … On | 00000000:AF:00.0 Off | N/A |
    | 27% 29C P8 13W / 250W | 3MiB / 11264MiB | 0% Default |
    | | | N/A |
    ±------------------------------±---------------------±---------------------+

±----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
±----------------------------------------------------------------------------+

  1. I tried to run PySpark to read sample data using CUDA cores. However, I do not know whether the PySpark REALLY call CUDA cores or not. I run “nvidia-smi -l” and get same above output.

Any help and advice would be highly appreciated.