Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-level Sparsity via Mixture-of-Experts

Rishov Sarkar¹, Hanxue Liang², Zhiwen Fan², Zhangyang Wang², Cong Hao¹

¹School of Electrical and Computer Engineering, Georgia Institute of Technology
²School of Electrical and Computer Engineering, University of Texas at Austin

ICCAD 2023 paper

Overview

This is Edge-MoE, the first end-to-end FPGA accelerator for multi-task ViT with a rich collection of architectural innovations.