What is the latest CUDA version that support GeForce 450MX

Priyanka_Perera: <p>My GPU is TU117M [GeForce MX450]. What is the latest CUDA version I can use ?</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/2/e/2e18d33533d928fe9eba1a1a00b26dd8e88e89da.png" data-download-href="https://discuss.pytorch.org/uploads/default/2e18d33533d928fe9eba1a1a00b26dd8e88e89da" title="image"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/2/e/2e18d33533d928fe9eba1a1a00b26dd8e88e89da_2_690x187.png" alt="image" data-base62-sha1="6zN9mx5oW8n09V64PWCUfMNRRoe" width="690" height="187" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/2/e/2e18d33533d928fe9eba1a1a00b26dd8e88e89da_2_690x187.png, https://discuss.pytorch.org/uploads/default/optimized/3X/2/e/2e18d33533d928fe9eba1a1a00b26dd8e88e89da_2_1035x280.png 1.5x, https://discuss.pytorch.org/uploads/default/optimized/3X/2/e/2e18d33533d928fe9eba1a1a00b26dd8e88e89da_2_1380x374.png 2x" data-dominant-color="351029"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image</span><span class="informations">1850×502 76.6 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>Thanks</p>

ptrblck: <p>Your MX450 uses the Turing architecture with compute capability 7.5 and is thus supported in all currently released stable and nightly PyTorch binaries.</p>

Priyanka_Perera: <p>Ok, that’s interesting to know.</p>
<p>I’m using <code>torch 2.0.1</code> which cuda <a href="https://download.pytorch.org/whl/cu118" rel="noopener nofollow ugc">https://download.pytorch.org/whl/cu118</a> but I’m still receiving <code>torch.cuda.is_enabled()</code> False due to <code>torch._C._cuda_getDeviceCount() &gt;</code> returning 0.</p>
<p>Any insights on what I’m missing here?</p>
<pre><code class="lang-auto">[[tool.poetry.source]]
name = "default"
url = "https://pypi.org/simple"

[[tool.poetry.source]]
name = "pytorch"
url = "https://download.pytorch.org/whl/cu118"
secondary = true

[tool.poetry.dependencies]
..
python = "~3.10.12"
pytorch-forecasting = { version = "=1.0.0", source = "default" }
..
tensorboard = { version = "*", source = "default"}
tensorboardX = { version = "*", source = "default"}
torch = { version = "=2.0.1", source = "pytorch" }
</code></pre>

ptrblck: <p>What does <code>torch.version.cuda</code> return?</p>

Priyanka_Perera: <p><code>torch.version.cuda</code> returns <code>11.8</code></p>

Priyanka_Perera: <p>Do I need any other prerequisite?</p>
<p>My driver is <code>nvidia-driver-545</code></p>

Priyanka_Perera: <p>I upgraded to torch 2.1.0 (torch.version.cuda = 12.1) and still <code>torch._C._cuda_getDeviceCount()</code> returns 0.</p>
<p>I also have below libraries installed.</p>
<pre><code class="lang-auto">❯ apt list --installed | grep cuda

WARNING: apt does not have a stable CLI interface. Use with caution in scripts.

cuda-cccl-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-command-line-tools-12-3/unknown,now 12.3.0-1 amd64 [installed,automatic]
cuda-compiler-12-3/unknown,now 12.3.0-1 amd64 [installed,automatic]
cuda-crt-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-cudart-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-cudart-dev-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-cuobjdump-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-cupti-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-cupti-dev-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-cuxxfilt-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-documentation-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-driver-dev-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-gdb-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-keyring/unknown,now 1.1-1 all [installed]
cuda-libraries-12-3/unknown,now 12.3.0-1 amd64 [installed,automatic]
cuda-libraries-dev-12-3/unknown,now 12.3.0-1 amd64 [installed,automatic]
cuda-nsight-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nsight-compute-12-3/unknown,now 12.3.0-1 amd64 [installed,automatic]
cuda-nsight-systems-12-3/unknown,now 12.3.0-1 amd64 [installed,automatic]
cuda-nvcc-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvdisasm-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvml-dev-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvprof-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvprune-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvrtc-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvrtc-dev-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvtx-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvvm-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-nvvp-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-opencl-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-opencl-dev-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-profiler-api-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-sanitizer-12-3/unknown,now 12.3.52-1 amd64 [installed,automatic]
cuda-toolkit-12-3-config-common/unknown,now 12.3.52-1 all [installed,automatic]
cuda-toolkit-12-3/unknown,now 12.3.0-1 amd64 [installed]
cuda-toolkit-12-config-common/unknown,now 12.3.52-1 all [installed,automatic]
cuda-toolkit-config-common/unknown,now 12.3.52-1 all [installed,automatic]
cuda-tools-12-3/unknown,now 12.3.0-1 amd64 [installed,automatic]
cuda-visual-tools-12-3/unknown,now 12.3.0-1 amd64 [installed,automatic]
</code></pre>

Priyanka_Perera: <p>Hmm interestingly <code>torch.cuda.current_device()</code> returned an error.</p>
<pre><code class="lang-auto">RuntimeError                              Traceback (most recent call last)
Cell In[16], line 1
----&gt; 1 torch.cuda.current_device()

File ~/.cache/pypoetry/virtualenvs/vfm-nn-DOmiObSy-py3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:769, in current_device()
    767 def current_device() -&gt; int:
    768     r"""Returns the index of a currently selected device."""
--&gt; 769     _lazy_init()
    770     return torch._C._cuda_getDevice()

File ~/.cache/pypoetry/virtualenvs/vfm-nn-DOmiObSy-py3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:298, in _lazy_init()
    296 if "CUDA_MODULE_LOADING" not in os.environ:
    297     os.environ["CUDA_MODULE_LOADING"] = "LAZY"
--&gt; 298 torch._C._cuda_init()
    299 # Some of the queued calls may reentrantly call _lazy_init();
    300 # we need to just return without initializing in that case.
    301 # However, we must not let any *other* threads in!
    302 _tls.is_initializing = True

RuntimeError: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx
</code></pre>

Priyanka_Perera: <p>I had a default xorg driver from Ubuntu. I installed the below driver downloaded from NVIDIA and that worked.</p>
<p><a class="mention" href="/u/ptrblck">@ptrblck</a> thanks for helping me to debug on the right path!</p>
<p>±--------------------------------------------------------------------------------------+<br>
| NVIDIA-SMI 535.113.01             Driver Version: 535.113.01   CUDA Version: 12.2     |<br>
|-----------------------------------------±---------------------±---------------------+<br>
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |<br>
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |<br>
|                                         |                      |               MIG M. |<br>
|=========================================+======================+======================|<br>
|   0  NVIDIA GeForce MX450           Off | 00000000:01:00.0 Off |                  N/A |<br>
| N/A   60C    P0              N/A / ERR! |      5MiB /  2048MiB |      0%      Default |<br>
|                                         |                      |                  N/A |<br>
±----------------------------------------±---------------------±---------------------+</p>
<p>±--------------------------------------------------------------------------------------+<br>
| Processes:                                                                            |<br>
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |<br>
|        ID   ID                                                             Usage      |<br>
|=======================================================================================|<br>
|    0   N/A  N/A      3136      G   /usr/lib/xorg/Xorg                            4MiB |<br>
±--------------------------------------------------------------------------------------+</p>

ptrblck: <p>Good to hear it’s working now!</p>
<p>Just to answer a few things for clarity:</p>
<aside class="quote no-group" data-username="Priyanka_Perera" data-post="6" data-topic="190852">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/priyanka_perera/48/61648_2.png" class="avatar"> Priyanka_Perera:</div>
<blockquote>
<p>Do I need any other prerequisite?</p>
</blockquote>
</aside>
<p>No, you would only need to install a compatible NVIDIA driver and the PyTorch binaries with CUDA support.</p>