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ChipStar 1.1 Released For Compiling & Running HIP/CUDA On SPIR-V

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  • ChipStar 1.1 Released For Compiling & Running HIP/CUDA On SPIR-V

    Phoronix: ChipStar 1.1 Released For Compiling & Running HIP/CUDA On SPIR-V

    ChipStar 1.1 was released this past week as one of the open-source projects to help in porting HIP and CUDA applications to support the industry-standard SPIR-V. ChipStar acts to get HIP/CUDA codes working on SPIR-V with OpenCL or Intel's oneAPI Level Zero...

    Phoronix, Linux Hardware Reviews, Linux hardware benchmarks, Linux server benchmarks, Linux benchmarking, Desktop Linux, Linux performance, Open Source graphics, Linux How To, Ubuntu benchmarks, Ubuntu hardware, Phoronix Test Suite

  • #2
    There's always freaking C++. Finding good Vulkan, SDL tutorials for C is almost impossible.

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    • #3
      Looking forward to being able to run apps on more than just cuda and AMD's shittier "I can't beleive it's not cuda."

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      • #4
        Originally posted by Volta View Post
        There's always freaking C++. Finding good Vulkan, SDL tutorials for C is almost impossible.
        Depending on what you want to do you could also check out wgpu as an alternative.
        While the end result is probably not as fast as using Vulkan directly, you get something very portable that's most likely faster than using OpenGL.

        Native WebGPU implementation based on wgpu-core. Contribute to gfx-rs/wgpu-native development by creating an account on GitHub.


        While the tutorial is for C++, the API is C, so it shouldn't be much of a problem to translate the C++isms

        Resulting code: step005 WebGPU is a Render Hardware Interface(RHI), which means that it is a programming library meant to provide a unified interface for multiple underlying graphics hardware and o...

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        • #5
          Originally posted by oleid View Post

          Depending on what you want to do you could also check out wgpu as an alternative.
          While the end result is probably not as fast as using Vulkan directly, you get something very portable that's most likely faster than using OpenGL.

          Native WebGPU implementation based on wgpu-core. Contribute to gfx-rs/wgpu-native development by creating an account on GitHub.


          While the tutorial is for C++, the API is C, so it shouldn't be much of a problem to translate the C++isms

          https://eliemichel.github.io/LearnWe...lo-webgpu.html
          Thanks! It look really straightforward and it's just a 'simple' header for nice graphic manipulations.

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