Efficient Image Processing with Halide Presented by Adrián Palacios

Introduction

• Image processing is a topic where optimization matters.

• But optimization for multiple platforms is hard and expensive.

• We want tools for obtaining high-performance code regardless of the platform.

• Halide is a tool that aims to solve this problem.

Data-parallel and IP languages

• Data-parallel languages: • CUDA and OpenCL propose a SIMD

programming model for multi-core CPUs and GPUs.

• Implementations can be very efficient at the cost of losing portability.

• IP languages: • MATLAB and other suites release kernel

languages.

• But individual kernels are not enough.

Concretely, the problem is…

And the solution is…

The Halide language

• Halide is a functional programming language (“à la Haskell”) for IP.

• It makes a distinction between the algorithm and the 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 for generating 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 results Normal sized image Time (ms) Time / Halide Time (%)

Halide 8.486 1.000

ImageMagick 64.000 7.542

MATLAB 10.359 1.221

Mathematica 13.000 1.532

OpenCV 2 0.577 0.067

Big sized image Time (ms) Time / Halide Time (%)

Halide 188.829 1.000

ImageMagick 1748 9.257

MATLAB 192.501 1.019

Mathematica 1586 8.399

OpenCV 2 76.626 0.405

Gaussian blur

Gaussian blur results Normal sized image Time (ms) Time / Halide Time (%)

Halide 2.674 1.000

ImageMagick 304.000 113.687

MATLAB 2.834 1.059

Mathematica 117.003 43.755

OpenCV 2 1.076 0.402

Big sized image Time (ms) Time / Halide Time (%)

Halide 219.274 1.000

ImageMagick 12265 55.935

MATLAB 277.388 1.265

Mathematica 199203 908.466

OpenCV 2 191.875 0.875

Conclusions

• Halide beats each other tool (except OpenCV 2).

• There’s a lot of room for improvement.

• Programming with Halide is hard-to-learn, easy-to-master.

Questions?

• Halide’s repository at Github:

• https://github.com/halide/Halide