Generate High Performance SIMD Code on Intel from Simulink Blocks in DSP System Toolbox
To configure a Simulink® model to generate SIMD code on Intel®:
In the Modeling tab of the model toolstrip, click Model Settings.
In the Configuration Parameters dialog box that opens, in the Code Generation pane, set the System target file to
This workflow does not support the MinGW C/C++ compiler. You can choose any other compiler listed in Supported Compilers. To select a different compiler that is installed on your machine, run
mex -setupin the MATLAB® command prompt and follow the instructions.
Under Code Generation, in the Interface pane, set the Code Replacement libraries to either
DSP Intel AVX2-FMA (Windows),
DSP Intel AVX2-FMA (Linux), or
DSP Intel AVX2-FMA (Mac). Using these libraries, you can generate high performance SIMD code. For more information on Code Replacement Libraries, see What Is Code Replacement? (Embedded Coder).
In the model window, initiate code generation and the build process for the model by using one of these common options:
Click the Build Model button.
For an example on how to select a system target file for a Simulink model and how to generate C code for embedded systems, see Generate Code Using Embedded Coder (Embedded Coder).
The SIMD code is generated using Intel AVX2-FMA technology. The Intel AVX2 SIMD intrinsics significantly improve the performance of the code generated from the supported algorithms on Intel platforms, in most cases meeting or exceeding the performance of the simulation and plain C code.
Compare the Performance of SIMD Code with Generated Plain C Code
Consider this Simulink model that models a digital communication system. The model contains a root-raised cosine filter on the transmitter and the receiver side, a couple of FIR Interpolation and FIR Decimation blocks to increase and decrease the sample rate of the signal, respectively, and an additive white Gaussian noise (AWGN) communication channel to transmit the signal. The root-raised cosine filters on both sides perform matched filtering. The combined response of the two root-raised cosine filters forms a raised-cosine filter, which helps in minimizing the intersymbol interference (ISI). Due to matched filtering, the signal received at the output has a high signal to noise ratio (SNR) and low probability of error. To confirm, view the output in the constellation diagram that follows.
To open the model, type
ex_qam_matchedfilter in the MATLAB command prompt.
In the Modeling tab of the model, click Model
Settings. In the configuration parameters window that opens, under
Code Generation in the Interface pane,
set Code replacement libraries to
None. Build the model and this setting generates
plain C code executable in the current MATLAB directory. However, if you specify a code generation folder (Simulink) in Simulink preferences, building the model generates plain C code executable in
the specified folder. Measure the time it takes to run the executable.
tic; system('ex_qam_matchedfilter'); tplain = toc
tplain = 37.4883
Repeat the process by setting the Code replacement libraries
DSP Intel AVX2-FMA (Windows),
AVX2-FMA (Linux), or
DSP Intel AVX2-FMA
(Mac), depending on the platform of the machine you are using.
Build the model and measure the time it takes to run the generated AVX2
tic; system('ex_qam_matchedfilter'); tavx2 = toc
tavx2 = 8.29
The generated SIMD code is around 4.5x compared to the plain C code on a Windows® 10 machine.
ans = 4.5221