Efficient Image Processing with Halide
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Efficient Image Processing with Halide

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Efficient Image Processing with Halide Efficient Image Processing with Halide Presentation Transcript

  • Efficient ImageProcessing withHalidePresented by Adrián Palacios
  • Introduction• Image processing is a topicwhere optimization matters.• But optimization for multipleplatforms is hard andexpensive.• We want tools for obtaininghigh-performance coderegardless of the platform.• Halide is a tool that aims tosolve this problem.
  • Data-parallel and IP languages• Data-parallel languages:• CUDA and OpenCL propose a SIMDprogramming model for multi-core CPUsand GPUs.• Implementations can be very efficient atthe cost of losing portability.• IP languages:• MATLAB and other suites release kernellanguages.• But individual kernels are not enough.
  • Concretely, the problem is…
  • And the solution is…
  • The Halide language• Halide is a functional programming language (“àla Haskell”) for IP.• It makes a distinction between the algorithm andthe schedule:• The algorithm is what should be done.• The schedule is how it should be done.• Optimization is achieved by:• Using LLVM for generating simple code.• Using architecture-specific compilers forgenerating vectorized and parallel code.
  • Evaluation of Halide• Halide’s execution time is measured against:• ImageMagick.• MATLAB.• Mathematica.• OpenCV 2.• Two test images:• A normal sized image (512x512).• A big sized image (6400x4800).• For two methods:• RGB to grayscale.• Gaussian blur.
  • RGB to grayscale
  • RGB to grayscale resultsNormal sized image Time (ms) Time / Halide Time (%)Halide 8.486 1.000ImageMagick 64.000 7.542MATLAB 10.359 1.221Mathematica 13.000 1.532OpenCV 2 0.577 0.067Big sized image Time (ms) Time / Halide Time (%)Halide 188.829 1.000ImageMagick 1748 9.257MATLAB 192.501 1.019Mathematica 1586 8.399OpenCV 2 76.626 0.405
  • Gaussian blur
  • Gaussian blur resultsNormal sized image Time (ms) Time / Halide Time (%)Halide 2.674 1.000ImageMagick 304.000 113.687MATLAB 2.834 1.059Mathematica 117.003 43.755OpenCV 2 1.076 0.402Big sized image Time (ms) Time / Halide Time (%)Halide 219.274 1.000ImageMagick 12265 55.935MATLAB 277.388 1.265Mathematica 199203 908.466OpenCV 2 191.875 0.875
  • Conclusions• Halide beats each other tool(except OpenCV 2).• There’s a lot of room forimprovement.• Programming with Halide ishard-to-learn, easy-to-master.
  • Questions?• Halide’s repository at Github:• https://github.com/halide/Halide