convolutional neural networks 1efficiency optimization 1embedded hardware 1model compression 1pruning 1
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cs.AR2026★ 6 cited
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation
Shuo Huai, Hao Kong, Xiangzhong Luo +5
Crossbar-based In-Memory Processing (IMP) accelerators achieve high-speed, low-power computing for deep neural networks (DNNs), but face three obstacles. First, floating-point (FP)…
cs.AR2025
Learning Cache Coherence Traffic for NoC Routing Design
Guochu Xiong, Xiangzhong Luo, Weichen Liu
The rapid growth of multi-core systems highlights the need for efficient Network-on-Chip (NoC) design to ensure seamless communication. Cache coherence, essential for data consiste…