Accelerating Simulink/Matlab projects with SYCL

Abstract

Matlab/Simulink is a very popular software development tool which is widely used in academia and industry to build and evaluate complex dynamical systems. It combines graphical modelling with the ability to develop algorithms directly in the Matlab language and offers various toolboxes targeting a wide range of applications in automotive, robotics, image processing, machine learning and other areas. For deployment on various platforms the Matlab/Simulink projects are typically translated into C/C++ by MathWorks’ Simulink/Matlab Coder tool and subsequently built by the C/C++ toolchain for the targeted platform. In this talk we present a new tool flow to accelerate Simulink/Matlab projects with SYCL. This enables Matlab/Simulink projects to take advantage of the growing open-source SYCL ecosystem to accelerate complex Simulink models on a wide range of diverse platforms in a standards-based way. This enables Matlab/Simulink projects to directly benefit from performance-optimized SYCL algorithms and tools to tune the performance of Simulink models on different hardware. The presented tool flow does not require Matlab/Simulink to be installed and no Matlab/Simulink dependencies are required. The approach is non-disruptive in that the Simulink/Matlab developers do not need to know SYCL and do not need to adapt Simulink/Matlab solutions to take advantage of SYCL. In this work Simulink/Matlab solutions are translated with the help of open-source tools into C++ code calling an API which can be customized to use different algorithms and libraries as backends. For example, vector/matrix operations are typically performed in this flow by the Eigen library while scalar operations are performed by the standard C++ library. API functions for specific Matlab/Simulink operations or operands can be implemented or overloaded/specialized to use different libraries if needed. For example operations on large matrices or vectors can be implemented using SYCL-BLAS to take advantage of highly parallel linear algebra operations that can be autotuned to maximize performance for a given platform. The presented tool flow converts entire Simulink solutions into C++ code. It does so by reading in Simulink solutions files (in.slx or.mdl format) and extracting the models and their associated sub models and blocks. It also reads in and integrates data files (*.mat files), data dictionary files, and Matlab files to initialize the workspace. The blocks are then scheduled and translated into C++ code constituting the model step which is run to execute the model. Models can contain sub models, model references and sub systems – which can contain embedded Matlab files that are executed when the associated blocks are executed. These Matlab files are converted into C++ code and integrated with the code generated from the containing Simulink block. The tool flow solved various challenges when converting Matlab code into C++, and supports most Matlab language features. The presented tool flow has already been applied to accelerate complex Matlab/Simulink models in automotive projects: developed as part of a collaboration project with Williams Advanced Engineering the tool flow was used to accelerate large Simulink models of novel hybrid battery types for Electric Vehicles via SYCL. These models run on an embedded platform directly on the battery and acceleration enables more complex and accurate models to be run. This presentation shows the tool flow applied to opensource Simulink/Matlab code. We will present the results at SYCLcon. Performance varies by use, configuration and other factors. Your costs and results may vary.