38 citations · 42 across the 8 of their papers we have counts for
10 papers · 1 filter
A Framework for Accelerating Transformer Inference on RISC-V for Edge AI
Ajay Kumar M, Vishnu PS, Yike Li +5
This work presents a framework for accelerating transformer-based language models (LMs) on resource-constrained IoT devices. The framework targets compact LMs: BERT-Tiny (B-Ty), Mo…
A Pipelined FPGA Architecture for Banded Sparse Matrix Dense Matrix Multiplication in Longformer
Phillip Pramberger, Athanasios Tziouvaras, Shreejith Shanker +1
Sparse attention mechanisms have become increasingly important for transformer models processing long input sequences due to their lower computational and memory complexity compare…
Reinforcement Learning-Based Optimization of Workload-Aware Power Delivery Networks
Oran Hayes, Maria Pantazi-Kypraiou, Athanasios Tziouvaras +4
Power Delivery Networks (PDNs) are critical components of modern VLSI chips, providing stable voltage levels while satisfying electromigration (EM) and IR-drop constraints. Convent…
Co-Optimizing Graph Sparsification and Approximate Computing for Energy-Efficient FPGA-Based GCN Inference
Nathaniel Kaye Mellor, Shreejith Shanker, George Floros
Graph Convolutional Networks (GCNs) have emerged as a powerful framework for learning from graph-structured data, yet their deployment on resource-constrained edge platforms remain…
FINNAS: FINN-Guided Hardware-Aware NAS and Pruning for FPGA Jet Substructure Classification
Eva Chauffour, Changhong Li, Georgios Floros +1
FPGAs are well suited to deploying quantised neural networks (QNNs) under strict accuracy, latency, and resource constraints; however, identifying efficient model-accelerator combi…
FSNIC: A Low-Latency Flow-Based Intrusion Detection Architecture for FPGA SmartNICs
Nise O'Cuill, Changhong Li, Georgios Floros +1
Modern data centres require high-performance networking alongside effective real-time security. Traditional Intrusion Detection Systems (IDS) commonly rely on general-purpose proce…
EBL: Efficient Broad Learning for Distributed Adaptive Harmonic Analysis
Changhong Li, Georgios Floros, Biswajit Basu +1
Renewable energy systems and electrified transport have found widespread adoption in recent years. The integration of these non-linear loads, dominated by electric vehicle (EV) cha…
Model Predictive Current Control with Harmonic Correction for Single-Phase AC-DC EV Charging
Changhong Li, Bharathkumar Hegde, Biswajit Basu +1
The increasing integration of Electric Vehicles (EVs) has imposed a growing harmonic challenge on the power grid. For AC/DC Power Factor Correction (PFC) in single-phase On-Board C…
RQP: Resource-Oriented Quantiser Pruning for Neural Networks on FPGAs
Changhong Li, Biswajit Basu, Shreejith Shanker
High granularity quantisation (HGQ) exploits weight-level quantisation and pruning to design resource-efficient neural network accelerators, achieving an attractive trade-off betwe…
Workload-Aware Early-Stage Power Delivery Network Optimization via Architectural Power Traces
Oran Hayes, Maria Pantazi-Kypraiou, Athanasios Tziouvaras +4
Power Delivery Networks (PDNs) are critical for maintaining voltage integrity in modern multiprocessor systems. Conventional early-stage PDN planning relies on static or worst-case…