Graphics Programming weekly - Issue 345 - June 23rd, 2024


[video] GDC 2024 - GPU Work Graphs: Welcome to the Future of GPU Programming

  • the GDC video presents a discussion of the new work graph features for D3D (also a Vulkan AMD-specific extension exists)
  • explains the issue with the current ExecuteIndirect model
  • shows an overview of the API model and how it aims to solve the challenges
  • presents an overview of a compute shader rasterizer and a runtime GPU scattering system based on the technology
  • additionally discusses the support level


CPU performance optimization guide – part 1

  • the first blog in a series about CPU optimizations
  • this part presents how different implementations of max between floats can generate very different code
  • presents the effect of branch misprediction on performance and how to use the AMD profiler to detect through hardware counters


[video] I3D 2024 Papers Session 6 - Efficient Forward and Differentiable Rendering

  • the video recording of I3D 2024 sessions covers the following papers
  • Efficient Particle-Based Fluid Surface Reconstruction Using Mesh Shaders and Bidirectional Two-Level Grids,  ShaderPerFormer: Platform-independent Context-aware Shader Performance Predictor
  • Transforming a Non-Differentiable Rasterizer into a Differentiable One with Stochastic Gradient Estimation
  • these papers cover a focus on performance from an academic focus


Jobs

C++ Gameplay and UI Programmers

Auckland, New Zealand

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[video] Triangle Visibility Buffer 2.0

  • the talk provides an overview of the experimental Triangle Visibility Buffer 2.0 implementation
  • The presented approach uses only compute shaders to write the visibility buffer
  • discusses the pipeline design, different approaches based on triangle sizes, and how performance compares
  • additionally presents which features are still missing compared to hardware rasterization


From microfacets to participating media: A unified theory of light transport with stochastic geometry

  • the paper presents a method that aims to unify microfacets and volumes for light transport purposes
  • the paper shows that both can be expressed as stochastic implicit surfaces (SIS) and, more specifically, Gaussian process implicit surfaces (GPIS)
  • discusses the derivation, representation generation, and tracing aspects of GPIS
  • additionally discusses limitations regarding performance and quality


5 Reasons Why Box Plots are the Better Default Choice for Visualizing Performance

  • the blog post presents why the author suggests using box plots over bar charts as the default way to represent performance
  • shows annotated examples of how box plots can express a lot of helpful information in a concise form


Thanks to Jon Greenberg for support of this series.


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