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.