10 citations · 13 across the 3 of their papers we have counts for
4 papers
A Digital SRAM-Based Compute-In-Memory Macro for Weight-Stationary Dynamic Matrix Multiplication in Transformer Attention Score Computation
Jianyi Yu, Tengxiao Wang, Yuxuan Wang +6
Compute-in-memory (CIM) techniques are widely employed in energy-efficient artificial intelligent (AI) processors. They alleviate power and latency bottlenecks caused by extensive…
COMET: Towards Partical W4A4KV4 LLMs Serving
Lian Liu, Haimeng Ren, Long Cheng +6
Quantization is a widely-used compression technology to reduce the overhead of serving large language models (LLMs) on terminal devices and in cloud data centers. However, prevalen…
CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Accelerators
Songyun Qu, Shixin Zhao, Bing Li +4
In recent years, various computing-in-memory (CIM) processors have been presented, showing superior performance over traditional architectures. To unleash the potential of various…
Variation Enhanced Attacks Against RRAM-based Neuromorphic Computing System
Hao Lv, Bing Li, Lei Zhang +2
The RRAM-based neuromorphic computing system has amassed explosive interests for its superior data processing capability and energy efficiency than traditional architectures, and t…