Intel A770 GPU + Debian13 -- XPU available: False

5

Hello Franck,

Thank you very much for your reply. I think my problem is coming from the fact that there is no integration of intel tools with Debian 13 so far, and so even

$ clinfo | grep "Device Name"

output… nothing. so my guess is pytorch is working well, but it can’t locate all required intel components to access the GPU.

Franck, what is the output of

$uname -ar

and

$sudo apt-cache policy libze1

on your ‘working’ machine ?

Thank you !

Frédéric

EDIT : Problem solved ! as previously guessed all essential Intel Compute Runtime components were missing, without any warning or errors potentially helping to find such problem

So I followed the Intel Compute Runtime procedure, downloaded all *.deb files from the 25.44.36015.8 release and installed it. I added my user name in the ‘render’ group and ‘voilà’ :slight_smile:

$ clinfo | grep "Device Name"
  Device Name                                     Intel(R) Arc(TM) A770 Graphics
    Device Name                                   Intel(R) Arc(TM) A770 Graphics
    Device Name                                   Intel(R) Arc(TM) A770 Graphics
    Device Name                                   Intel(R) Arc(TM) A770 Graphics
$ python
Python 3.14.2 (main, Dec 18 2025, 14:49:47) [GCC 14.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.xpu.is_available())
True

so for anyone with a clean install of Debian 13, first step is to install all this stuff and then to install pytorch with the -xpu extension. As a reminder here is my working configuration:

$uname -ar
Linux THOR 6.18.2-1-liquorix-amd64 #1 ZEN SMP PREEMPT_DYNAMIC liquorix 6.18-1.1~trixie (2025-12-24) x86_64 GNU/Linux
$pip install torch==2.9.1+xpu torchvision==0.24.1+xpu torchaudio==2.9.1+xpu intel-cmplr-lib-rt intel-cmplr-lib-ur intel-cmplr-lic-rt intel-sycl-rt pytorch-triton-xpu tcmlib umf intel-pti --index-url https://download.pytorch.org/whl/xpu

and to test it:

>>> print(f"PyTorch version: {torch.__version__}")
PyTorch version: 2.9.1+xpu
>>> print(f"XPU available: {torch.xpu.is_available()}")
XPU available: True
>>> print(f"Device count: {torch.xpu.device_count()}")
Device count: 1
>>> print(f"Device name: {torch.xpu.get_device_name(0)}")
Device name: Intel(R) Arc(TM) A770 Graphics
>>> x = torch.randn(1000, 1000, device='xpu')
>>> y = torch.randn(1000, 1000, device='xpu')
>>> result = torch.mm(x, y)  # Matrix multiplication on Intel GPU
>>> print(f"✅ GPU computation successful on: {result.device}")
✅ GPU computation successful on: xpu:0

thank you so much for your help :slight_smile:

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