Build & install from source
To build the components of vAccel we need the vAccelRT core library and a backend plugin that implements the operation we want to execute.
This repo includes the core runtime
exec backend plugin and a debug plugin for testing (
1. Cloning and preparing the build directory
In Ubuntu-based systems, you need to have the following packages to build
You can install them using the following command:
sudo apt-get install -y cmake build-essential
Get the source code for vaccelrt:
git clone https://github.com/cloudkernels/vaccelrt --recursive
Prepare the build directory:
cd vaccelrt mkdir build cd build
2. Building the core runtime library
# This sets the installation path to /usr/local, and the current build # type to 'Release'. The other option is the 'Debug' build cmake ../ -DCMAKE_INSTALL_PREFIX=/usr/local -DCMAKE_BUILD_TYPE=Release make make install
3. Building the plugins
Building the plugins is disabled, by default. You can enable building one or
more plugins at configuration time of CMake by setting the corresponding
variable of the following table to
cmake -DBUILD_PLUGIN_NOOP=ON ..
will enable building the noop backend plugin.
Building a vaccel application
We will use an example of image classification which can be found under the examples folder of this project.
You can build the example using the following directive in the build directory:
cmake -DBUILD_EXAMPLES=ON .. make
A number of example binaries have been built:
# ls examples classify detect exec_generic minmax pose pynq_parallel segment_generic tf_inference classify_generic depth detect_generic minmax_generic pose_generic pynq_vector_add sgemm tf_model depth_generic exec Makefile noop pynq_array_copy segment sgemm_generic tf_saved_model
If, instead, you want to build by hand you need to define the include and
library paths (if they are not in your respective default search paths) and
also link with
$ cd ../examples $ gcc -Wall -Wextra -I/usr/local/include -L/usr/local/lib classify.c -o classify -lvaccel -ldl $ ls classify.c classify classify.c classify
Running a vaccel application
Having built our
classify example, we need to prepare the vaccel environment for it to run:
- Define the path to
libvaccel.so(if not in the default search path):
- Define the backend plugin to use for our application.
In this example, we will use the noop plugin:
- Finally, you can do:
./classify images/example.jpg 1
which should dump the following output:
$ ./classify images/example.jpg 1 Initialized session with id: 1 Image size: 79281B [noop] Calling Image classification for session 1 [noop] Dumping arguments for Image classification: [noop] len_img: 79281 [noop] will return a dummy result classification tags: This is a dummy classification tag!
Alternatively from the build directory:
$ cd ../build $ ./examples/classify ../examples/images/example.jpg 1 Initialized session with id: 1 Image size: 79281B [noop] Calling Image classification for session 1 [noop] Dumping arguments for Image classification: [noop] len_img: 79281 [noop] will return a dummy result classification tags: This is a dummy classification tag!