Power-Aware FPGA Mapping of Convolutional Neural Networks. - Alexander Montgomerie-Corcoran; Stylianos I. Venieris; Christos-Savvas Bouganis (FPT, 2019)

DEF: Differential Encoding of Featuremaps for Low Power Convolutional Neural Network Accelerators. - Alexander Montgomerie-Corcoran; Christos-Savvas Bouganis (ASP-DAC, 2021)

POMMEL: Exploring Off-Chip Memory Energy & Power Consumption in Convolutional Neural Network Accelerators. - Alexander Montgomerie-Corcoran; Christos-Savvas Bouganis (DSD, 2021)

SAMO: Optimised Mapping of Convolutional Neural Networks to Streaming Architectures. - Alexander Montgomerie-Corcoran; Zhewen Yu; Christos-Savvas Bouganis (FPL, 2022)

HARFLOW3D: A Latency-Oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices. - Petros Toupas; Alexander Montgomerie-Corcoran; Christos-Savvas Bouganis; Dimitrios Tzovaras (FCCM, 2023)

PASS: Exploiting Post-Activation Sparsity in Streaming Architectures for CNN Acceleration. - Alexander Montgomerie-Corcoran; Zhewen Yu; Jianyi Cheng; Christos-Savvas Bouganis (FPL, 2023)

SATAY: A Streaming Architecture Toolflow for Accelerating YOLO Models on FPGA Devices. - Alexander Montgomerie-Corcoran; Petros Toupas; Zhewen Yu; Christos-Savvas Bouganis (ICFPT, 2023)

Fast Prototyping Next-Generation Accelerators for New ML Models using MASE: ML Accelerator System Exploration. - Jianyi Cheng; Cheng Zhang; Zhewen Yu; Alexander Montgomerie-Corcoran; Can Xiao; Christos-Savvas Bouganis; Yiren Zhao (CoRR, 2023)

HASS: Hardware-Aware Sparsity Search for Dataflow DNN Accelerator. - Zhewen Yu; Sudarshan Sreeram; Krish Agrawal; Junyi Wu; Alexander Montgomerie-Corcoran; Cheng Zhang; Jianyi Cheng; Christos-Savvas Bouganis; Yiren Zhao (FPL, 2024)