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MATLAB Coder: How do I build the Arm CMSIS-NN library for Deep Learning C code generation and deployment?

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I see a few deep learning networks supported for code generation using MATLAB Coder:
I'm looking to generate code from my deep learning network to run on Arm Cortex-M CPUs using MATLAB Coder and the Arm CMSIS-NN library. What are the steps to do this?

Respuesta aceptada

Bill Chou
Bill Chou el 29 de Jun. de 2022
To generate and run C code for deep neural networks on Cortex-M hardware, you must have the CMSIS-NN library. See the post below for instructions on building the library:

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Bill Chou
Bill Chou el 14 de Mzo. de 2022
Editada: Bill Chou el 29 de Jun. de 2022
This is an old answer that has since been updated, and is kept here for reference only. Please see this post for up-to-date instructions.
To generate and run C code for deep neural networks on Cortex-M hardware, you must have the CMSIS-NN (Cortex Microcontroller Software Interface Standard - Neural Networks) library. This following describes the build steps for CMSIS-NN on Windows and Linux platforms that use a cross-compiler toolchain.
Requirements
To build the CMSIS-NN static library, you must first create a makefile. Copy the following code snippet into a file and save it as Makefile.mk. This sample makefile builds the CMSIS-NN library for the Cortex-M7 core. To build the library for other targets, modify the CFLAGS variable as appropriate for your target hardware.
STATIC_LIB_DIR=./lib
STATIC_LIB_FILE_NAME = libcmsisnn.a
CFLAGS= -fPIC -c -mcpu=cortex-m7 -Ofast -DNDEBUG
INC = -I../Core/Include -I../DSP/PrivateInclude -I../DSP/Include -I../NN/Include
rwildcard=$(foreach d,$(wildcard $(1:=/*)),$(call rwildcard,$d,$2) $(filter $(subst *,%,$2),$d))
SOURCE_FILES = $(call rwildcard,Source,*.c)
OBJECT_FILES = $(patsubst %.c,%.o,$(wildcard $(SOURCE_FILES)))
$(STATIC_LIB_FILE_NAME): $(OBJECT_FILES)
ar -r -o $(STATIC_LIB_DIR)/$@ $^
#Compiling every *.c to *.o
%.o: %.c dirmake
arm-none-eabi-gcc -c $(INC) $(CFLAGS) -o $@ $<
dirmake:
@mkdir -p $(STATIC_LIB_DIR)
clean:
rm -f $(OBJECT_FILES) $(STATIC_LIB_DIR)/$(STATIC_LIB_FILE_NAME)
Note: Make sure that Makefile was written properly, using the above code, and following makefile indentation rules.
We have validated the CMSIS-NN library build process below using:
  • Windows platform: GNU Arm Embedded Toolchain version 10.3.1
  • Linux platform: GNU Arm Embedded Toolchain version 8.3.0
Linux Platform
1. Install the open-source GNU Arm Embedded Toolchain provided by ARM (See https://developer.arm.com/tools-and-software/open-source-software/developer-tools/gnu-toolchain/gnu-rm for more information).
2. Download the source code for CMSIS version 5.7.0 (available at https://github.com/ARM-software/CMSIS_5/archive/refs/tags/5.7.0.zip).
3. Unzip the source code to a folder and follow these steps to build and generate the static library:
  • Open a Linux terminal.
  • Change directory to the CMSIS-NN source folder by running this command. Here, <CMSIS Root folder> points to the extracted CMSIS folder.
cd <CMSIS Root folder>/CMSIS/NN
  • Copy the Makefile.mk file that you created to the current directory.
  • Run the makefile by using the make command.
make -f Makefile.mk
  • Running the makefile creates the static library libcmsisnn.a in the ./lib folder.
4. Configure the MATLAB environment to generate code that uses the CMSIS-NN library:
  • At /usr/local, create a folder named cmsisnn.
  • Copy the header files located at <CMSIS Root folder>/CMSIS/DSP/Include and <CMSIS Root folder>/CMSIS/NN/Include to the location /usr/local/cmsisnn/include.
  • Copy the generated static library located at <CMSIS Root folder>/CMSIS/NN/Include to the location /usr/local/cmsisnn/lib.
  • At the MATLAB command window, set the MATLAB environment variable CMSISNN_PATH to the location of the CMSIS-NN install folder.
setenv('CMSISNN_PATH’, ‘/usr/local/cmsisnn’)
Windows Platform
1. Install open-source GNU Arm Embedded Toolchain provided by ARM (available at https://developer.arm.com/-/media/Files/downloads/gnu-rm/10.3-2021.10/gcc-arm-none-eabi-10.3-2021.10-win32.exe).
2. Download and install the 'build system(make.exe)' and 'archiving(ar.exe)' tools. We have tested this step by using Cygwin (available at https://www.cygwin.com/) to run the makefile.
3. Download the source code for CMSIS version 5.7.0 (available at https://github.com/ARM-software/CMSIS_5/archive/refs/tags/5.7.0.zip).
4. Unzip the source code to a folder, and follow these steps to build and generate the static library:
  • Open a Windows command prompt.
  • Change directory to the CMSIS-NN source folder by running this command. Here, <CMSIS Root folder> points to the extracted CMSIS folder.
cd <CMSIS Root folder>\CMSIS\NN
  • Copy the Makefile.mk file that you created to the current directory.
  • Run the makefile by using the make command.
make -f Makefile.mk
  • Running the makefile creates the static library libcmsisnn.a in the .\lib folder.
5. Configure the MATLAB environment to generate code that uses the CMSIS-NN library:
  • At C:\Program Files, create a folder named cmsisnn.
  • Copy the header files located at <CMSIS Root folder>\CMSIS\DSP\Include and <CMSIS Root folder>\CMSIS\NN\Include to the location C:\Program Files\cmsisnn\include.
  • Copy the generated static library located at <CMSIS Root folder>\CMSIS\NN\Include to the location C:\Program Files\cmsisnn\lib.
  • At the MATLAB command window, set the MATLAB environment variable CMSISNN_PATH to the location of the CMSIS-NN install folder.
setenv('CMSISNN_PATH’, ‘C:\Program Files\cmsisnn’)

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