Less for More: Reducing Intra-CGRA Connectivity for Higher Performance and Efficiency in HPC
Boma Anantasatya Adhi, Carlos Cortes, Emanuele Del Sozzo, Tomohiro Ueno, Yiyu Tan, Takuya Kojima, Artur Podobas, Kentaro Sano · 2023
Coarse-Grained Reconfigurable Arrays (CGRAs) are a class of reconfigurable architectures that inherit the performance of Domain-specific accelerators and the reconfigurability aspects of Field-Programmable Gate Arrays (FPGAs). Historically, CGRAs have been successfully used to accelerate embedded applications and are now considered to accelerate High-Performance Computing (HPC) applications in future supercomputers. However, embedded systems and supercomputers are two vastly different domains with different applications and constraints, and it is today not fully understood what CGRA design decisions adequately cater to the HPC market. One such unknown design decision is regarding the interconnect that facilitates intra-CGRA communication. Our findings show that even the typical king-style mesh-like topology is often under-utilized with a typical HPC workload, leading to inefficiency. This research aims to explore the provisioning of intra-CGRA interconnect for HPC-oriented workloads and, ultimately, recoup the potential performance and efficiency lost by reducing the interconnect complexity. We proposed several reduced interconnect topologies based on the usage statistic. Then we evaluate the tradeoffs regarding hardware cost, routability of DFGs, and computational throughput.