I’ve got an arch linux, with two GPU in the laptop (thinkpad P14s Gen 4) + a new RTX 3090 plugged via thunderbolt 4 with the Cool Master EG200 GPU enclosure:
❯ lspci -k | grep -A 2 -E "(VGA|3D)"
00:02.0 VGA compatible controller: Intel Corporation Raptor Lake-P [Iris Xe Graphics] (rev 04)
Subsystem: Lenovo Raptor Lake-P [Iris Xe Graphics]
Kernel driver in use: i915
--
03:00.0 3D controller: NVIDIA Corporation GA107GLM [RTX A500 Laptop GPU] (rev a1)
Subsystem: Lenovo GA107GLM [RTX A500 Laptop GPU]
Kernel driver in use: nvidia
--
22:00.0 VGA compatible controller: NVIDIA Corporation GA102 [GeForce RTX 3090] (rev a1)
Subsystem: Gigabyte Technology Co., Ltd GA102 [GeForce RTX 3090]
Kernel driver in use: nvidia
The thunderbolt connection to the RTX 3090 is authorized as you can see here:
❯ sudo boltctl info c4010000-0070-740e-0362-00168691c921
[sudo] password for aemonge:
● Cooler Master Technology,Inc MasterCase EG200
├─ type: peripheral
├─ name: MasterCase EG200
├─ vendor: Cooler Master Technology,Inc
├─ uuid: c4010000-0070-740e-0362-00168691c921
├─ dbus path: /org/freedesktop/bolt/devices/c4010000_0070_740e_0362_00168691c921
├─ generation: Thunderbolt 3
├─ status: authorized
│ ├─ domain: 69078780-60ab-fe2a-ffff-ffffffffffff
│ ├─ parent: 69078780-60ab-fe2a-ffff-ffffffffffff
│ ├─ syspath: /sys/devices/pci0000:00/0000:00:0d.2/domain0/0-0/0-1
│ ├─ rx speed: 40 Gb/s = 2 lanes * 20 Gb/s
│ ├─ tx speed: 40 Gb/s = 2 lanes * 20 Gb/s
│ └─ authflags: boot
├─ authorized: Wed 24 Jan 2024 06:49:10 AM UTC
├─ connected: Wed 24 Jan 2024 06:49:10 AM UTC
└─ stored: Tue 23 Jan 2024 03:50:50 PM UTC
├─ policy: iommu
└─ key: no
I really don’t care for the graphics, nor the RTX3090 to be loaded in the xorg nor the graphical interface. I just want it to be used as compute only workloads, and I have followed thouroly this arch wiki External GPU - ArchWiki
But givien that context, my nvidia-smi can’t seam to find the GPU:
❯ nvidia-smi -L
GPU 0: NVIDIA RTX A500 Laptop GPU (UUID: GPU-762410c2-1c0d-ef4a-89ac-91afd926381b)
Nor can a simple python script, cuda-devices.py:
❯ cat cuda-devics.py
import torch
# Check if CUDA is available
if torch.cuda.is_available():
print("CUDA is available.")
# Get the number of CUDA devices
num_devices = torch.cuda.device_count()
print(f"Number of CUDA devices: {num_devices}")
# Get the name of each CUDA device
for i in range(num_devices):
print(f"Device {i} name: {torch.cuda.get_device_name(i)}")
else:
print("CUDA is not available.")
❯ python cuda-devics.py
CUDA is available.
Number of CUDA devices: 1
Device 0 name: NVIDIA RTX A500 Laptop GPU
❯ CUDA_VISIBLE_DEVICES="0,1,2" python cuda-devics.py
CUDA is available.
Number of CUDA devices: 1
Device 0 name: NVIDIA RTX A500 Laptop GPU
I have also tried with these three repositories GitHub - ewagner12/all-ways-egpu: Configure eGPU as primary under Linux Wayland desktops , GitHub - karli-sjoberg/gswitch and GitHub - hertg/egpu-switcher: 🖥🐧 Setup script for eGPUs in Linux (X.Org). To disable the internal GPU’s A500 and Iris Xe but it’s blaking (black screen).