9 citations · 19 across the 15 of their papers we have counts for
4 papers · 1 filter
Norm-Q: Effective Compression Method for Hidden Markov Models in Neuro-Symbolic Applications
Hanyuan Gao, Xiaoxuan Yang
Hidden Markov models (HMM) are commonly used in generation tasks and have demonstrated strong capabilities in neuro-symbolic applications for the Markov property. These application…
Titanus: Enabling KV Cache Pruning and Quantization On-the-Fly for LLM Acceleration
Peilin Chen, Xiaoxuan Yang
Large language models (LLMs) have gained great success in various domains. Existing systems cache Key and Value within the attention block to avoid redundant computations. However,…
AutoRAC: Automated Processing-in-Memory Accelerator Design for Recommender Systems
Feng Cheng, Tunhou Zhang, Junyao Zhang +6
The performance bottleneck of deep-learning-based recommender systems resides in their backbone Deep Neural Networks. By integrating Processing-In-Memory~(PIM) architectures, resea…
Optimizing and Exploring System Performance in Compact Processing-in-Memory-based Chips
Peilin Chen, Xiaoxuan Yang
Processing-in-memory (PIM) is a promising computing paradigm to tackle the "memory wall" challenge. However, PIM system-level benefits over traditional von Neumann architecture can…