Translating structured sequential programs to dataflow graphs
Klaus Schneider · 2021
In this paper, a translation from structured sequential programs to equivalent dataflow process networks (DPNs) is presented that is based on a carefully chosen set of nodes including load/store operations to access a shared global memory. For every data structure stored in the main memory, we use corresponding tokens to enforce the sequential ordering of load/store operations accessing that data structure as far as needed. Except for the load/store nodes, all nodes obey the Kahn principle so that they are deterministic in the sense that the same inputs are always mapped to the same outputs regardless of the execution schedule of the nodes. Due to the sequential ordering of load/store nodes, determinacy is also maintained by them. Moreover, the generated DPNs are quasi-static, i.e., they have schedules that are bounded in a very strict sense: For every statement of the sequential program, the corresponding DPN behaves like a homogeneous synchronous actor, i.e., it consumes one value of each input port and will finally provide one value on each output port. Hence, no more than one value needs to be stored in each buffer.