Evaluating Architectural Trade-offs in CGRAs: The Impact of Scratchpad Memory and Heterogeneity on Compute-Intensive Kernels (opens in new tab)

Modern edge computing applications, particularly high-throughput stream processing like Vision Transformers (ViTs), demand massive spatial parallelism and efficient data movement under tight power and area constraints. Coarse-Grained Reconfigurable Architectures (CGRAs) offer a promising paradigm to balance performance, flexibility, and energy efficiency. This paper analyzes the impact of two critical CGRA design choices: processing element hete...