CLUMAP: Clustered Mapper for CGRAs with Predication

Coarse-grained reconfigurable architectures (CGRAs) have gained popularity as accelerators for compute-intensive kernels. Complex CGRA architectures that support key features such as multi-context and predication are being developed to support a wider range of kernels. However, mapping applications on these complex architectures poses significant challenges. In this paper, we provide an architecture-agnostic clustered mapping technique and a new cost function tailored for simulated-annealing placement. The mapper simplifies placement and routing phases, demonstrating significant speedup for popular CGRA architectures: HyCUBE and ADRES. Additionally, our method demonstrates an increase in mapping success for the ADRES architecture.