MatCL - OpenCL MATLAB Interface
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1 MatCL - OpenCL MATLAB Interface MatCL - OpenCL MATLAB Interface Slide 1
2 MatCL - OpenCL MATLAB Interface OpenCL toolkit for Mathworks MATLAB/SIMULINK Compile & Run OpenCL Kernels Handles OpenCL memory management MatCL - OpenCL MATLAB Interface Slide 2
3 MathWorks MATLAB Commercial Numerical Computing Environment Engineering, Science, Economics Free GNU Octave clone Native C/C++ interface MEX Support for CUDA (2010) No OpenCL support MatCL - OpenCL MATLAB Interface Slide 3
4 MatCL Easy to use MATLAB OpenCL toolkit Wraps OpenCL low-level API Single instruction to copy memory & build, run Kernels Support all standard OpenCL devices Intended for Kernel development & MATLAB acceleration Easy way to try out & learn OpenCL MatCL - OpenCL MATLAB Interface Slide 4
5 MatCL Features MATLAB R2014a and up (GNU Octave support) Windows, Linux, macos Native support for MATLAB datatypes (scalar & vector) Compiler output & Kernel printf redirection Support for OpenCL 2.x pipes Precompiled binaries available on GitHub MatCL - OpenCL MATLAB Interface Slide 5
6 MatCL Basic Usage Get Device info: Available devices with type (CPU,GPU) Available memory Possible WG & LW sizes Number of compute units per device MatCL - OpenCL MATLAB Interface Slide 6
7 MatCL Basic Usage Compile & Run kernel automatically Quick & Easy way to test kernels Compile & Run Kernel separately Intended to run kernels repeatedly MATLAB acceleration MatCL - OpenCL MATLAB Interface Slide 7
8 Kernel Development & Validation Problem: Intended Host application unsuitable for development (HPC Clusters, Embedded Platforms, FPGAs ) Develop Kernels using predefined input data & check results Advantages of MATLAB: Provides data I/O (HDF5, XML, MPEG, JPG, PNG, SQL ) Provides graphical output/plotting tools Comprehensive numerical toolbox for data generation & validation MatCL - OpenCL MATLAB Interface Slide 8
9 Example: Kernel Development Numerical Plasma Simulation Complex indexing Multi-Layer boundary handling Requires specific input data MatCL - OpenCL MATLAB Interface Slide 9
10 MATLAB Code Acceleration MPI based code parallelization using parfor Only data parallelism No parallelization for built-in functions Native CUDA support (since 2010) Some built-in functions supported directly Support for custom CUDA code Easy entry for CUDA beginners No support for AMD & Intel GPUs OpenCL support missing MatCL - OpenCL MATLAB Interface Slide 10
11 Example: 2D Median Filter Typical use: image noise removal, edge detection Built-in MATLAB function: medfilt2 MATLAB CUDA version available OpenCL implementation using MatCL MatCL - OpenCL MATLAB Interface Slide 11
12 Example: 2D Median Filter Typical use: image noise removal, edge detection Problem size: 1200x1200 uint8 Built-in MATLAB function: medfilt2 Systems: Core i7-7700hq/gtx1050/intel HD Graphics 630 Ryzen X/GTX1060 MATLAB (CPU) MATLAB (CUDA) MatCL - CPU MatCL GPU1 MatCL GPU2 Core i GTX1050/HD 630 Ryzen X GTX ms 3 ms 5 ms 1.8 ms 5 ms 25 ms 3 ms 2 ms 2.5 ms - MatCL - OpenCL MATLAB Interface Slide 12
13 Example: Cross Correlation Typical use: pattern recognition, echo cancelation Problem size: float Built-in MATLAB function: xcorr Systems: Core i7-7700hq/gtx1050/intel HD Graphics 630 Ryzen X/GTX1060 MATLAB (CPU) MATLAB (CUDA) MatCL - CPU MatCL GPU1 MatCL GPU2 Core i GTX1050/HD 630 Ryzen X GTX ms 70 ms 8 ms 6 ms 12 ms 68 ms 745 ms(?) 9 ms 4 ms - MatCL - OpenCL MATLAB Interface Slide 13
14 Still ahead Detailed documentation & more examples Complicated build system (library conflicts) No native 16-bit half-precision support (deep learning) Grapics support (context sharing)? Cooperation with MathWorks (official hardware support package)? Spread the word MatCL - OpenCL MATLAB Interface Slide 14
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