Sep 9, 2023 · This framework integrates integer-only quantization, crossbar-aligned pruning, and runtime-aware non-ideality adaptation schemes into one ...
Oct 21, 2024 · Crossbar-based In-Memory Processing (IMP) accelerators have been widely adopted to achieve high-speed and low-power computing, ...
Title: CRIMP: compact & reliable DNN inference on in-memory processing via crossbar-aligned compression and non-ideality adaptation. Authors: Huai, Shuo
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation. S Huai, H Kong, X Luo, S Li, R ...
Jan 31, 2023 · Crossbar-based In-Memory Computing (IMC) accelerators preload the entire Deep Neural Network (DNN) into crossbars before inference.
CRIMP: compact & reliable DNN inference on in-memory processing via crossbar-aligned compression and non-ideality adaptation · Huai, Shuo; Kong, Hao; Luo ...
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation · Shuo Huai, Hao Kong, Xiangzhong ...
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation · Shuo HuaiHao Kong +5 authors
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation. 2023, ACM Transactions on ...
Network quantization is a popular method that can reduce the memory and computation cost of networks by using low-precision fixed-point parameters and low-cost ...