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cs.AR2025
NX-CGRA: A Programmable Hardware Accelerator for Core Transformer Algorithms on Edge Devices
Rohit Prasad
The increasing diversity and complexity of transformer workloads at the edge present significant challenges in balancing performance, energy efficiency, and architectural flexibili…
cs.AR2025
An ultra-low-power CGRA for accelerating Transformers at the edge
Rohit Prasad
Transformers have revolutionized deep learning with applications in natural language processing, computer vision, and beyond. However, their computational demands make it challengi…
cs.AR2025★ 1 cited
J3DAI: A tiny DNN-Based Edge AI Accelerator for 3D-Stacked CMOS Image Sensor
Benoit Tain, Raphael Millet, Romain Lemaire +9
This paper presents J3DAI, a tiny deep neural network-based hardware accelerator for a 3-layer 3D-stacked CMOS image sensor featuring an artificial intelligence (AI) chip integrati…