Mapping computation kernels to clustered programmable-reconfigurable processors

Reconfigurable computing systems have shown the potential to surpass conventional processor architectures in performance for a growing range of applications. That performance, however, must be attained without significantly changing the design effort on the programmer´s part, and without drastically increasing compilation time. In this paper, we present our compiler framework for mapping computation kernels to the reconfigurable clusters of Amalgam, a clustered programmable-reconfigurable processor. We first promote the use of the gated singular-assignment program dependence graph, a parallel intermediate program representation, to represent computation kernels. We then present an algorithm for mapping a computation kernel into the control FSM and datapath for a reconfigurable cluster. Finally, we describe our fast datapath synthesis tool-flow which preserves regularity and reduces the problem size by not flattening the datapath to gates.