2 papers
cs.AR2026
Model Compression and Hardware-Aware Acceleration for Deep Learning on FPGAs: A Co-Design Taxonomy and Comparative Analysis
Peter Forcha, H. Kajekusumadhar, Mbua Peter +3
Deploying deep neural networks on Field-Programmable Gate Arrays (FPGAs) requires joint reasoning about model compression and hardware acceleration, however the most comprehensive…
cs.AR2026
MAGMA: Mixture-Model Adaptive Gaussian Model Acceleration
Peter Forcha, Harshitha Kajekusumadhar, Mbua Peter +2
Conventional FPGA-based Gaussian Mixture Model (GMM) accelerators use offline-trained, fixed parameters, limiting their ability to adapt to evolving scene statistics in long-lived…