9 papers
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…
Bare-Metal RISC-V + NVDLA SoC for Efficient Deep Learning Inference
Vineet Kumar, Ajay Kumar M, Yike Li +2
This paper presents a novel System-on-Chip (SoC) architecture for accelerating complex deep learning models for edge computing applications through a combination of hardware and so…
LogicSparse: Enabling Engine-Free Unstructured Sparsity for Quantised Deep-learning Accelerators
Changhong Li, Biswajit Basu, Shreejith Shanker
FPGAs have been shown to be a promising platform for deploying Quantised Neural Networks (QNNs) with high-speed, low-latency, and energy-efficient inference. However, the complexit…
ReTiDe: Real-Time Denoising for Energy-Efficient Motion Picture Processing with FPGAs
Changhong Li, Clément Bled, Rosa Fernandez +1
Denoising is a core operation in modern video pipelines. In codecs, in-loop filters suppress sensor noise and quantisation artefacts to improve rate-distortion performance; in cine…