Genetic programming for shader simplification

Abstract

We present a framework based on Genetic Programming (GP) for automatically simplifying procedural shaders. Our approach computes a series of increasingly simplified shaders that expose the inherent trade-off between speed and accuracy. Compared to existing automatic methods for pixel shader simplification [Olano et al. 2003; Pellacini 2005], our approach considers a wider space of code transformations and produces faster and more faithful results. We further demonstrate how our cost function can be rapidly evaluated using graphics hardware, which allows tens of thousands of shader variants to be considered during the optimization process. Our approach is also applicable to multi-pass shaders and perceptual-based error metrics.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 01, 2011
Source ID
10.1145/2070781.2024186

Entities

People

  • Jason Lawrence
  • Nicholas Modly
  • Pitchaya Sitthi-amorn
  • Westley Weimer

Organizations

  • Air Force Office of Scientific Research
  • Defense Advanced Research Projects Agency
  • Division of Computing and Communication Foundations
  • University of Virginia

Tags

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Computer Vision.
  • Operations Research

Technology Areas

  • Biotechnology
  • Space