3 papers
cs.AR2026
Enabling Mixed criticality applications for the Versal AI-Engines
Vincent Sprave, Martin Wilhelm, Daniele Passaretti +2
Adaptive Systems-on-Chips (SoCs) are increasingly being used in mixed criticality systems (MCSs), such as in autonomous driving, aviation and medical systems. In this context, AMD…
cs.LG2025
Rescaling-Aware Training for Efficient Deployment of Deep Learning Models on Full-Integer Hardware
Lion Mueller, Alberto Garcia-Ortiz, Ardalan Najafi +2
Integer AI inference significantly reduces computational complexity in embedded systems. Quantization-aware training (QAT) helps mitigate accuracy degradation associated with post-…
cs.AR2025
VUSA: Virtually Upscaled Systolic Array Architecture to Exploit Unstructured Sparsity in AI Acceleration
Shereef Helal, Alberto Garcia-Ortiz, Lennart Bamberg
Leveraging high degrees of unstructured sparsity is a promising approach to enhance the efficiency of deep neural network DNN accelerators - particularly important for emerging Edg…