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20242026
most citedBare-Metal RISC-V + NVDLA SoC for Efficient Deep Learning Inference

2 citations · 5 across the 3 of their papers we have counts for

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cs.AR2025★ 1 cited

MARVEL: An End-to-End Framework for Generating Model-Class Aware Custom RISC-V Extensions for Lightweight AI

Ajay Kumar M, Cian O'Mahoney, Pedro Kreutz Werle +5

Deploying deep neural networks (DNNs) on resource-constrained IoT devices remains a challenging problem, often requiring hardware modifications tailored to individual AI models. Ex…

cs.AR2025★ 2 cited

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…