CONFERM: Recurrence-Aware Temporal Mapping for Multi-Cycle Multi-Context CGRAs
Throughput in DSP and machine learning workloads is often limited by two temporal structures, i.e., loop-carried recurrences and long-latency, multi-cycle compute nodes. On spatio-temporal coarse-grained reconfigurable arrays (CGRAs), both bottlenecks can be addressed by overlapping iterations across the multi-context...