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  1. In the previous blog post we discussed a few potential neural network (MLP) applications in rendering and one of the conclusions was that although easy to implement, inference cost can be quite high, especially for larger networks which makes a compute sh…

  2. Adventures in Neural Rendering

    In recent years, neural networks have started to find their way into many areas of rendering.

  3. Subdividing a 3D space into cells or voxels and using positional and/or directional information to directly index into it is a popular method to store and access local data, typically using 3D textures.

  4. Following up on the previous post on GPU utilization and performance, and to provide a practical example, I expanded a bit on a topic discussed in brief: vertex shader exports and their impact on performance.

  5. Drill deep into a GPU’s architecture and at its heart you will find a large number of SIMD units whose purpose is to read data, perform some vector or scalar ALU (VALU or SALU) operation on it and write the result out to a rendertarget or buffer.

  6. Async compute all the things

    GPUs make work parallelism very easy by design: each drawcall/dispatch shader instruction operates on batches of vertices, pixels, threads in general at the same time automatically.

  7. Meshlets and Mesh Shaders

    Mesh shaders, introduced back in 2018 as an NVidia Turing and later as an AMD RDNA2 feature, is an evolution of the geometry pipeline which removes a number of fixed function units like the Input Assembler and Tessellator as well as the Vertex shader/Doma…

  8. I posted a few days ago a screenshot of the long shader ISA code produced by the RGA compiler for a single atan2() instruction.

  9. In the previous blog post I described a simple workgraph implementation of a hybrid shadowing system.

  10. A quick introduction to workgraphs

    Workgraphs is a new feature added recently to DirectX12 with hardware support from NVidia and AMD.