<story><title>AMD&apos;s CDNA 3 Compute Architecture</title><url>https://chipsandcheese.com/2023/12/17/amds-cdna-3-compute-architecture/</url></story><parent_chain><item><author>Const-me</author><text>&amp;gt; the consumer cards don&amp;#x27;t do compute?&lt;p&gt;Typically, software developers only support a single GPGPU API, and that API is nVidia CUDA.&lt;p&gt;Technically, consumer AMD cards are awesome at compute. For example, UE5 renders triangle meshes with compute instead of graphics &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.youtube.com&amp;#x2F;watch?v=TMorJX3Nj6U&quot; rel=&quot;nofollow noreferrer&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.youtube.com&amp;#x2F;watch?v=TMorJX3Nj6U&lt;/a&gt; Moreover, AMD cards often outperform nVidia equivalents because nVidia prioritized ray tracing and DLSS over compute power and memory bandwidth.&lt;p&gt;The issue is, no tech company is interested in adding D3D or Vulkan backend to AI libraries like PyTorch. nVidia is not doing that because they are happy with the status quo. Intel and AMD are not doing that because both hope to replace CUDA with their proprietary equivalents, instead of an open GPU API.</text></item><item><author>jdewerd</author><text>&amp;gt; AMD diverged their GPU architecture development into separate CDNA and RDNA lines specialized for compute and graphics respectively.&lt;p&gt;Ooooh, is that why the consumer cards don&amp;#x27;t do compute? Yikes, I was hoping that was just a bit of misguided segmentation but this sounds like a high level architecture problem, like an interstate without an on ramp. Oof.</text></item></parent_chain><comment><author>GeekyBear</author><text>&amp;gt; The issue is, no tech company is interested in adding D3D or Vulkan backend to AI libraries like PyTorch.&lt;p&gt;AMD is interested in making PyTorch take advantage of their chips, and has done so.&lt;p&gt;&amp;gt; we are delighted that the PyTorch 2.0 stable release includes support for AMD Instinct™ and Radeon™ GPUs that are supported by the ROCm™ software platform.&lt;p&gt;When NVIDIA is charging 1000% profit margins for a GPU aimed at use as an AI accelerator, you can expect competitors to be willing to do what it takes to move into that market.&lt;p&gt;&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.tomshardware.com&amp;#x2F;news&amp;#x2F;nvidia-makes-1000-profit-on-h100-gpus-report&quot; rel=&quot;nofollow noreferrer&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.tomshardware.com&amp;#x2F;news&amp;#x2F;nvidia-makes-1000-profit-o...&lt;/a&gt;</text></comment>
<story><title>AMD&apos;s CDNA 3 Compute Architecture</title><url>https://chipsandcheese.com/2023/12/17/amds-cdna-3-compute-architecture/</url></story><parent_chain><item><author>Const-me</author><text>&amp;gt; the consumer cards don&amp;#x27;t do compute?&lt;p&gt;Typically, software developers only support a single GPGPU API, and that API is nVidia CUDA.&lt;p&gt;Technically, consumer AMD cards are awesome at compute. For example, UE5 renders triangle meshes with compute instead of graphics &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.youtube.com&amp;#x2F;watch?v=TMorJX3Nj6U&quot; rel=&quot;nofollow noreferrer&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.youtube.com&amp;#x2F;watch?v=TMorJX3Nj6U&lt;/a&gt; Moreover, AMD cards often outperform nVidia equivalents because nVidia prioritized ray tracing and DLSS over compute power and memory bandwidth.&lt;p&gt;The issue is, no tech company is interested in adding D3D or Vulkan backend to AI libraries like PyTorch. nVidia is not doing that because they are happy with the status quo. Intel and AMD are not doing that because both hope to replace CUDA with their proprietary equivalents, instead of an open GPU API.</text></item><item><author>jdewerd</author><text>&amp;gt; AMD diverged their GPU architecture development into separate CDNA and RDNA lines specialized for compute and graphics respectively.&lt;p&gt;Ooooh, is that why the consumer cards don&amp;#x27;t do compute? Yikes, I was hoping that was just a bit of misguided segmentation but this sounds like a high level architecture problem, like an interstate without an on ramp. Oof.</text></item></parent_chain><comment><author>zozbot234</author><text>Vulkan Compute backends for numerical compute (as typified by both OpenCL and SYCL) are challenging, you can look at clspv &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;google&amp;#x2F;clspv&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;google&amp;#x2F;clspv&lt;/a&gt; project for the nitty gritty details.  The lowest-effort path so far is most likely via some combination of Rocm&amp;#x2F;HIP (for hardware that AMD bothers to support themselves) and the Mesa project&amp;#x27;s RustiCL backend (for everything else).</text></comment>