8 citations · 14 across the 6 of their papers we have counts for
4 papers · 1 filter
WhiFlash: Accelerating Speculative Decoding with Token-Level Cross-Paradigm Routing
Young D. Kwon, Miles Williams, Rui Li +2
The autoregressive nature of large language models (LLMs) remains a significant bottleneck for inference, particularly in complex agentic workloads. While speculative decoding (SD)…
Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference
Hao Mark Chen, Wayne Luk, Ka Fai Cedric Yiu +4
The auto-regressive decoding of Large Language Models (LLMs) results in significant overheads in their hardware performance. While recent research has investigated various speculat…
TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge
Young D. Kwon, Rui Li, Stylianos I. Venieris +3
On-device training is essential for user personalisation and privacy. With the pervasiveness of IoT devices and microcontroller units (MCUs), this task becomes more challenging due…
The Future of Consumer Edge-AI Computing
Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris +2
In the last decade, Deep Learning has rapidly infiltrated the consumer end, mainly thanks to hardware acceleration across devices. However, as we look towards the future, it is evi…