Parallelism control scheme in a dataflow architecture

Abstract

We propose execution control scheme to realize an efficient multi-processing environment in dataflow architecture. With a unified software and hardware mechanism, we can detect states of processes at run time, which are treated as control information. We control the process level parallelism according to the hardware capacity, and virtualize high speed memory in dynamic data-driven computation where context changes in every instruction execution. We apply this scheme to the Datarol architecture, an optimized version of dynamic dataflow architecture, and evaluate them through software simulation.