<story><title>Cuda.jl v3.3: union types, debug info, graph APIs</title><url>https://juliagpu.org/post/2021-06-10-cuda_3.3/</url></story><parent_chain><item><author>xvilka</author><text>I wish more attention would be towards open source alternatives for CUDA, such as AMD&amp;#x27;s ROCm[1][2] and Julia framework using it - AMDGPU.jl[3]. It&amp;#x27;s sad to see so many people praise NVIDIA which is the enemy of open source, openly hostile to anything except their oversized proprietary binary blobs.&lt;p&gt;[1] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;rocmdocs.amd.com&amp;#x2F;en&amp;#x2F;latest&amp;#x2F;index.html&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;rocmdocs.amd.com&amp;#x2F;en&amp;#x2F;latest&amp;#x2F;index.html&lt;/a&gt;&lt;p&gt;[2] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;RadeonOpenCompute&amp;#x2F;ROCm&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;RadeonOpenCompute&amp;#x2F;ROCm&lt;/a&gt;&lt;p&gt;[3] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;JuliaGPU&amp;#x2F;AMDGPU.jl&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;JuliaGPU&amp;#x2F;AMDGPU.jl&lt;/a&gt;</text></item></parent_chain><comment><author>jpsamaroo</author><text>AMD has done great work in a very short amount of time, but let&amp;#x27;s not forget that they&amp;#x27;re still &lt;i&gt;very&lt;/i&gt; new to the GPU compute game. The ROCm stack is overall still pretty buggy, and definitely hard to build in ways other than what AMD deems officially supported.&lt;p&gt;As AMDGPU.jl&amp;#x27;s maintainer, I do certainly appreciate more users using AMDGPU.jl if they have the ability to, but I don&amp;#x27;t want people to think that it&amp;#x27;s anywhere close in terms of maturity, overall performance, and feature-richness compared to CUDA.jl. If you already have access to an NVIDIA GPU, it&amp;#x27;s painless to setup and should work really well for basically anything you want to with it. I can&amp;#x27;t say the same about AMDGPU.jl right now (although we are definitely getting there).</text></comment>
<story><title>Cuda.jl v3.3: union types, debug info, graph APIs</title><url>https://juliagpu.org/post/2021-06-10-cuda_3.3/</url></story><parent_chain><item><author>xvilka</author><text>I wish more attention would be towards open source alternatives for CUDA, such as AMD&amp;#x27;s ROCm[1][2] and Julia framework using it - AMDGPU.jl[3]. It&amp;#x27;s sad to see so many people praise NVIDIA which is the enemy of open source, openly hostile to anything except their oversized proprietary binary blobs.&lt;p&gt;[1] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;rocmdocs.amd.com&amp;#x2F;en&amp;#x2F;latest&amp;#x2F;index.html&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;rocmdocs.amd.com&amp;#x2F;en&amp;#x2F;latest&amp;#x2F;index.html&lt;/a&gt;&lt;p&gt;[2] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;RadeonOpenCompute&amp;#x2F;ROCm&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;RadeonOpenCompute&amp;#x2F;ROCm&lt;/a&gt;&lt;p&gt;[3] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;JuliaGPU&amp;#x2F;AMDGPU.jl&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;JuliaGPU&amp;#x2F;AMDGPU.jl&lt;/a&gt;</text></item></parent_chain><comment><author>krapht</author><text>Most people hack on this stuff for work, and time is money. OpenCL is just a lot less productive than CUDA for most tasks. The NVidia price premium isn&amp;#x27;t big enough to make people switch over.</text></comment>