FastFlow targeting FPGAs
Marco Danelutto, Gabriele Mencagli, Alberto Ottimo, F. Iannone, Paolo Palazzari · 2023
Writing good code for FPGA is a challenge “per se”, but also running already existing and optimized FPGA kernels often requires writing specific “host side” code and some target hardware knowledge to achieve good performances. In this work, we describe a FastFlow extension supporting seamless off loading of tasks to FPGA, once an FPGA kernel is available. In particular, we show how kernels implemented in Vitis and running on XILINX Alveo FPGA boards may be integrated to implement “normal” parallel stages (pipeline stages, map/farm workers) in a structured parallel FastFlow computation. Experimental results are shown, demonstrating the feasibility of the approach.