Accelerating Edge AI with Morpher: An Integrated Design, Compilation and
  Simulation Framework for CGRAs
Dhananjaya Wijerathne Zhaoying Li Tulika Mitra
Coarse-Grained Reconfigurable Arrays (CGRAs) hold great promise as
power-efficient edge accelerator, offering versatility beyond AI applications.
Morpher, an open-source, architecture-adaptive CGRA design framework, is
specifically designed to explore the vast design space of CGRAs. The
comprehensive ecosystem of Morpher includes a tailored compiler, simulator,
accelerator synthesis, and validation framework. This study provides an
overview of Morpher, highlighting its capabilities in automatically compiling
AI application kernels onto user-defined CGRA architectures and verifying their
functionality. Through the Morpher framework, the versatility of CGRAs is
harnessed to facilitate efficient compilation and verification of edge AI
applications, covering important kernels representative of a wide range of
embedded AI workloads. Morpher is available online at
https://github.com/ecolab-nus/morpher-v2.