4 papers
A Unified Geometric Field Theory Framework for Transformers: From Manifold Embeddings to Kernel Modulation
Xianshuai Shi, Jianfeng Zhu, Leibo Liu
The Transformer architecture has achieved tremendous success in natural language processing, computer vision, and scientific computing through its self-attention mechanism. However…
Gate-level boolean evolutionary geometric attention neural networks
Xianshuai Shi, Jianfeng Zhu, Leibo Liu
This paper presents a gate-level Boolean evolutionary geometric attention neural network that models images as Boolean fields governed by logic gates. Each pixel is a Boolean varia…
CAPSim: A Fast CPU Performance Simulator Using Attention-based Predictor
Buqing Xu, Jianfeng Zhu, Yichi Zhang +4
CPU simulators are vital for computer architecture research, primarily for estimating performance under different programs. This poses challenges for fast and accurate simulation o…
EFFACT: A Highly Efficient Full-Stack FHE Acceleration Platform
Yi Huang, Xinsheng Gong, Xiangyu Kong +8
Fully Homomorphic Encryption (FHE) is a set of powerful cryptographic schemes that allows computation to be performed directly on encrypted data with an unlimited depth. Despite FH…