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Build and run a vAccel application

Assuming we have an installation of vAccel, either by building from source or by installing the binary packages, we will walk through the process of running a simple vAccel application

Building a vaccel application

We will use an example of image classification which can be found under the examples folder of this project.

If you haven't already done so, get the code and prepare the build directory:

git clone https://github.com/cloudkernels/vaccelrt --recursive
cd vaccelrt
mkdir -p build
cd build

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 dl:

# Make sure to replace VACCEL_INSTALL with your current vAccel installation
# path, eg. ${HOME}/.local
export VACCEL_INSTALL=/usr/local
export VACCEL_LIBS=${VACCEL_INSTALL}/lib
export VACCEL_INCLUDES=${VACCEL_INSTALL}/include
cd ../examples
gcc -Wall -Wextra -I${VACCEL_INSTALL}include -L${VACCEL_INSTALL}/lib classify.c -o classify -lvaccel -ldl

You should be presented with the classify binary in the current directory:

$ 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:

1. Set library path

Define the path to libvaccel.so (if not in the default search path):

export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH

2. Set the plugin

Define the backend plugin to use for our application.

In this example, we will use the noop plugin:

export VACCEL_BACKENDS=/usr/local/lib/libvaccel-noop.so

3. Run the app

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!