By means of partial reconfiguration, parts of the hardware can be dynamically exchanged at runtime. This allows that streaming application running in different modes of the systems can share resources. In this paper, we discuss the architectural issues to design such reconfigurable systems. For being able to reduce reconfiguration time, this paper furthermore proposes a novel algorithm to aggregate several streaming applications into a single representation, called merge graph. The paper also proposes an algorithm to place streaming application at runtime which not only considers the placement and communication constraints, but also allows to place merge tasks. In a case study, we implement the proposed algorithm as runtime support on an FPGA-based system on chip. Furthermore, experiments show that reconfiguration time can be considerably reduced by applying our approach.
Probabilistic Performance Modelling when Using Partial Reconfiguration to Accelerate Streaming Applications with Non-deterministic Task Scheduling
