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.

翻译：粗粒度可重构阵列（CGRAs）作为能效型边缘加速器具有显著潜力，其应用范围可扩展至人工智能之外。Morpher作为一种开源且架构自适应的CGRA设计框架，专门用于探索CGRA的广阔设计空间。该框架的完整生态体系包含定制化编译器、仿真器、加速器综合及验证工具。本研究对Morpher进行综述，重点阐述其自动将AI应用内核编译至用户定义CGRA架构并进行功能验证的能力。通过Morpher框架，CGRA的灵活性得以充分发挥，可高效完成边缘AI应用的编译与验证，覆盖代表嵌入式AI工作负载关键场景的核心算子。Morpher开源代码获取地址：https://github.com/ecolab-nus/morpher-v2。