2 papers
eess.SY2024
ASCEND: Accurate yet Efficient End-to-End Stochastic Computing Acceleration of Vision Transformer
Tong Xie, Yixuan Hu, Renjie Wei +4
Stochastic computing (SC) has emerged as a promising computing paradigm for neural acceleration. However, how to accelerate the state-of-the-art Vision Transformer (ViT) with SC re…
cs.AR2024
Efficient yet Accurate End-to-End SC Accelerator Design
Meng Li, Yixuan Hu, Tengyu Zhang +4
Providing end-to-end stochastic computing (SC) neural network acceleration for state-of-the-art (SOTA) models has become an increasingly challenging task, requiring the pursuit of…