An Architecture-Agnostic Integer Linear Programming Approach to CGRA Mapping

Abstract

Coarse-grained reconfigurable architectures (CGRAs) have gained traction as a potential solution to implement accelerators for compute-intensive kernels, particularly in domains requiring hardware programmability. Architecture and CAD for CGRAs are tightly intertwined, with many prior works having combined architectures and tools. In this work, we present an architecture-agnostic integer linear programming (ILP) approach for CGRA mapping, integrated within an open-source CGRA architecture evaluation framework. The mapper accepts an application and an architecture description as input and can generate an optimal mapping, if indeed mapping is feasible. An experimental study demonstrates its effectiveness over a range of CGRA architectures.