part1_hls4ml_intro.md

Download and install the package

git clone https://github.com/FPGA4HEP/hls4ml.git
cd hls4ml
source install_miniconda3.sh
source ~/.bashrc
source install.sh

Every time you log in do:

source setup_hls4ml.sh
conda activate hls4ml-env

Run as well git pull to fetch the latest changes.

Run the tool (with your favourite model, e.g. 1-layer)

cd keras-to-hls
export FAVOURITEMODEL=1layer
python keras-to-hls.py -c keras-config-${FAVOURITEMODEL}.yml

This will create a folder called my-hls-test-${FAVOURITEMODEL}. If you want to change the projectory directory name edit the yml configuration file.

Run project design synthesis with Vivado HLS

cd my-hls-test-${FAVOURITEMODEL}
vivado_hls -f build_prj.tcl

If you get a runtime error from vivado, log out and prepend "LC_ALL=C" to your ssh command, ex.

LC_ALL=C ssh -i FPGA4HEP.pem centos@your-ip

Readout resource usage and latency from the synthesis report

cd ..
./print-reports.sh my-hls-test-${FAVOURITEMODEL}

Extract and compare area under the ROC curve from keras (floating point calculations) and HLS (fixed point calculations)

python extract_roc.py -c keras-config-${FAVOURITEMODEL}.yml

EXERCISE:

Change precision of calculations and reuse factor in the keras configuration file and check effect on NN performance (AUC) and FPGA resource usage using the scripts above.

ReuseFactor: N  # N = number of times a multiplier is used to do a computation 
DefaultPrecision: ap_fixed<X,Y>  # X = total number of bits, Y = number of integer bits, X-Y = number of decimal bits

NB: suggest to change the project output directory in the keras configuration for each test to avoid overwriting of previous projects.