Latency difference with same Model but version of hls4ml

Created by: sparajul

Quick summary

I was trying to find the FPGA resource usage and the latency with the CNN model i build, I used exact same setting and got completely different result with 0.6.0 and 0.7.1 version of hls4ml. While using 0.6.0-> the latency was around 1.2 us and While using 0.7.1-> the latency was around 7us, which is a huge difference.

Steps to Reproduce

I worked in the jupyter notebook. If needed here is the complete notebook. https://github.com/sparajul/fastmachinelearning/blob/main/TrainCNN.ipynb

import hls4ml import os model_cnn = load_model('cnn.h5') os.environ['PATH'] = '/tools/Xilinx/Vivado/2018.3/bin:' + os.environ['PATH']

hls_config = hls4ml.utils.config_from_keras_model(model_cnn, granularity='name')

hls_config['Model']['Precision'] = 'ap_fixed<16,8>' hls_config['Model']['ReuseFactor'] = 10

cfg = hls4ml.converters.create_config(backend='Vivado') cfg['IOType'] = 'io_stream' cfg['HLSConfig'] = hls_config cfg['KerasModel'] = model_cnn cfg['OutputDir'] = 'keras_cnn/vu13p'

cfg['XilinxPart'] = 'xcvu13p-flga2577-2L-e'

hls_model_aq = hls4ml.converters.keras_to_hls(cfg) hls_model_aq.compile()

hls_model_aq.build(csim=False, synth=True, vsynth=True)

hls4ml.report.read_vivado_report('keras_cnn/vu13p')

Actual behavior

Difference Latency in different version of hls4ml

#Saved model here cnn.h5.zip