GPU compatibility: mobile RTX A2000?

josmi9966: <p>I find it hard to understand which NVIDIA GPUs will work with which versions of PyTorch and under which OS.</p>
<p>For a project, somebody wants to purchase a laptop that has RTX A2000 built in and I am wondering which PyTorch versions this card would work with? Would it work under Ubuntu 22.04? Under Windows?<br>
If the spec shows it to use CUDA 8, will it still work with a current pytorch release that is compiled with cuda 11?</p>
<p>How can one find out in general if Card X will work with PyTorch versions X…Y under OS Z?</p>
<p>or looking at it from the other side, which laptop cards would work with current pytorch releases?</p>

ptrblck: <p>All NVIDIA GPUs &gt;= compute capability 3.7 will work with the latest PyTorch release with the CUDA 11.x runtime.</p>

josmi9966: <p>Thanks!<br>
Sadly the compute capability is not something NVIDIA seems to like to include in their specs, e.g.</p><aside class="onebox pdf" data-onebox-src="https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/rtx-a2000/nvidia-rtx-a2000-datasheet-1987439-r5.pdf">
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<p>Also this page, which has all kinds of info about many GPUs does not list the “compute capability”: <a href="https://www.techpowerup.com/gpu-specs/rtx-a2000-embedded.c3894" class="inline-onebox" rel="noopener nofollow ugc">NVIDIA RTX A2000 Embedded Specs | TechPowerUp GPU Database</a></p>
<p>But the specs say that the card is based on the Ampere architecture which seems to have compute capability 8, from which I assume that I should be fine for some time.</p>
<p>Is there a table somewhere which maps pytorch versions to the supported compute capabilities?<br>
Is there just a minimal compute capability version per pytorch version or is it a specific range of versions that is supported?</p>
<p>Thanks again!</p>

ptrblck: <aside class="quote no-group" data-username="josmi9966" data-post="3" data-topic="161318">
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<p>Sadly the compute capability is not something NVIDIA seems to like to include in their specs, e.g.</p>
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<p>You might want to check <a href="https://en.wikipedia.org/wiki/CUDA">CUDA - Wikipedia</a> as it shows the compute capabilities for (all) GPUs.</p>
<aside class="quote no-group" data-username="josmi9966" data-post="3" data-topic="161318">
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<img loading="lazy" alt="" width="24" height="24" src="https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/josmi9966/48/2272_2.png" class="avatar"> josmi9966:</div>
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<p>But the specs say that the card is based on the Ampere architecture which seems to have compute capability 8, from which I assume that I should be fine for some time.</p>
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<p>Yes, it’s an Ampere GPU with cc=8.6 and is supported.</p>
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<p>Is there a table somewhere which maps pytorch versions to the supported compute capabilities?</p>
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<p>No, I don’t think there is a mapping and we keep the min. cc=3.7 to support old K80 cards, which are still used in Colab if I’m not mistaken.<br>
Every newer Architecture is still supported and you can generally check the supported architectures via: <code>print(torch.cuda.get_arch_list())</code>.</p>
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<img loading="lazy" alt="" width="24" height="24" src="https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/josmi9966/48/2272_2.png" class="avatar"> josmi9966:</div>
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<p>Is there just a minimal compute capability version per pytorch version or is it a specific range of versions that is supported?</p>
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<p>The min. cc is <code>3.7</code> for (I believe) ~2 years now. It was bumped from 3.5 at one point, but I’m unsure when it was changed. Every newer architecture is supported.</p>

josmi9966: <p>Thank you, that is very helpful!</p>