The AMD “Aldebaran” GPU That Won Exascale

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • ROCm

    ROCm - Open Software Platform for GPU Compute

    ROCm 4.5 is also the last release to support their own Vega 10 based accelerator. (Radeon Instinct MI25)

    https://github.com/RadeonOpenCompute/ROCm#amd-instinct-mi25-...

    aka AMD doesn't care... they just want the supercomputer contracts where the customers are savvy enough to build their own very specific SW stack.

  • VkFFT

    Vulkan/CUDA/HIP/OpenCL/Level Zero Fast Fourier Transform library

    Incorrect. Vulkan has compute shaders[1], which are generally usable. Libraries like VkFFT[2] demonstrate basic signal processing in Vulkan. This can certainly be expanded upon, & there are numerous other non-graphical uses.

    There is a Vulkan ML TSG (Technical Subgroup), which is supposed to be working on ML. Even Nvidia is participating, with extensions like VK_NV_cooperative_matrix, which specifically target the ml tensor cores.

    There's people could probably say this better/more specifically, but I'll give it a try: Vulkan is, above all, an general standard for dispatching & orchestrating work usually on a GPU. Right now that work is most of often graphics, but that is far from a limit.

    SYCL is, imo, the opposite of where we need to go. It's the old historical legacy that CUDA has, of writing really dumb ignorant code & hoping the tools can make it run well on a GPU. Vulkan, on the other hand, asks us to consider deeply what near-to-the-metal resources we are going to need, and demands that we define, dispatch, & complete the actual processing engines on the GPU that will do the work. It's a much much much harder task, but it invites in fantastic levels of close optimization & tuning, allows for far more advanced pipelining & possibilities. If the future is good, it should abandon SYCL and CUDA, and bother to get good at Vulkan.

    [1] https://vkguide.dev/docs/gpudriven/compute_shaders/

    [2] https://github.com/DTolm/VkFFT

    [3] https://www.khronos.org/assets/uploads/developers/presentati...

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