A Near Optimal Integrated Solution for Resource Constrained Scheduling, Binding and Routing on CGRAs

Mapping problems to Coarse Grained Reconfigurable Arrays (CGRA) has been researched for many years now. Yet, no feasible mapping algorithms are known that can be considered optimal or even near optimal. The main reason for this deficit is the complex nature of the mapping problem. It can be considered as a combined scheduling, binding and routing problem. It involves several constraints that need to be handled at the same time: operator availability, storage space and interconnect. This becomes even more distinct if we consider inhomogeneous and irregular CGRAs. In this contribution we establish lower bounds for schedule lengths by employing the known optimal resource constrained scheduling approach BULB. We modify it such that it can handle the additional constraints of CGRAs. Although the runtime can get very long, this modified BULB scheduler can find near optimal schedules for all test cases. It is also able to handle real life applications like an ADPCM decoder consisting of more than 600 operations.