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cs.LG2026
PQuantML: A Tool for End-to-End Hardware-aware Model Compression
Roope Niemi, Anastasiia Petrovych, Arghya Ranjan Das +9
PQuantML is a new open-source, hardware-aware neural network model compression library tailored to end-to-end workflows. Motivated by the need to deploy performant models to enviro…
cs.LG2026
AIE4ML: An End-to-End Framework for Compiling Neural Networks for the Next Generation of AMD AI Engines
Dimitrios Danopoulos, Enrico Lupi, Chang Sun +4
Efficient AI inference on AMD's Versal AI Engine (AIE) is challenging due to tightly coupled VLIW execution, explicit datapaths, and local memory management. Prior work focused on…