2 papers
cs.LG2025
Convergence for Discrete Parameter Update Schemes
Paul Wilson, Fabio Zanasi, George Constantinides
Modern deep learning models require immense computational resources, motivating research into low-precision training. Quantised training addresses this by representing training com…
cs.AR2025
hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware
Jan-Frederik Schulte, Benjamin Ramhorst, Chang Sun +50
We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can b…