Baoting Li

ME-MoD: Algorithm-Hardware-Dataflow Co-Design for Memory Efficient Mixture-of-Depth-Based Vision Transformer Accelerator

Transformers outperform traditional neural networks but face high computational and memory costs, limiting edge device deployment. Although many hardware accelerators aim to address this, the original Transformer structure still restricts the optimization effect. A recent breakthrough, mixture-of-depths (MoDs), employs...