1 citations · 1 across the 4 of their papers we have counts for
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TorR: Towards Brain-Inspired Task-Oriented Reasoning via Cache-Oriented Algorithm-Architecture Co-design
Hyunwoo Oh, SungHeon Jeong, Suyeon Jang +4
Task-oriented object detection (TOOD) atop CLIP offers open-vocabulary, prompt-driven semantics, yet dense per-window computation and heavy memory traffic hinder real-time, power-l…
QUILL: An Algorithm-Architecture Co-Design for Cache-Local Deformable Attention
Hyunwoo Oh, Hanning Chen, Sanggeon Yun +5
Deformable transformers deliver state-of-the-art detection but map poorly to hardware due to irregular memory access and low arithmetic intensity. We introduce QUILL, a schedule-aw…
T-SAR: A Full-Stack Co-design for CPU-Only Ternary LLM Inference via In-Place SIMD ALU Reorganization
Hyunwoo Oh, KyungIn Nam, Rajat Bhattacharjya +7
Recent advances in LLMs have outpaced the computational and memory capacities of edge platforms that primarily employ CPUs, thereby challenging efficient and scalable deployment. W…
ASTER: Attention-based Spiking Transformer Engine for Event-driven Reasoning
Tamoghno Das, Khanh Phan Vu, Hanning Chen +2
The integration of spiking neural networks (SNNs) with transformer-based architectures has opened new opportunities for bio-inspired low-power, event-driven visual reasoning on edg…
Neuro-Photonix: Enabling Near-Sensor Neuro-Symbolic AI Computing on Silicon Photonics Substrate
Deniz Najafi, Hamza Errahmouni Barkam, Mehrdad Morsali +6
Neuro-symbolic Artificial Intelligence (AI) models, blending neural networks with symbolic AI, have facilitated transparent reasoning and context understanding without the need for…