3 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
Prosperity: Accelerating Spiking Neural Networks via Product Sparsity
Chiyue Wei, Cong Guo, Feng Cheng +4
Spiking Neural Networks (SNNs) are highly efficient due to their spike-based activation, which inherently produces bit-sparse computation patterns. Existing hardware implementation…
A Survey: Collaborative Hardware and Software Design in the Era of Large Language Models
Cong Guo, Feng Cheng, Zhixu Du +21
The rapid development of large language models (LLMs) has significantly transformed the field of artificial intelligence, demonstrating remarkable capabilities in natural language…
NDSEARCH: Accelerating Graph-Traversal-Based Approximate Nearest Neighbor Search through Near Data Processing
Yitu Wang, Shiyu Li, Qilin Zheng +5
Approximate nearest neighbor search (ANNS) is a key retrieval technique for vector database and many data center applications, such as person re-identification and recommendation s…
Block-Wise Mixed-Precision Quantization: Enabling High Efficiency for Practical ReRAM-based DNN Accelerators
Xueying Wu, Edward Hanson, Nansu Wang +9
Resistive random access memory (ReRAM)-based processing-in-memory (PIM) architectures have demonstrated great potential to accelerate Deep Neural Network (DNN) training/inference.…