Partitioned scheduling of periodic real-time tasks onto reconfigurable hardware

Abstract

Reconfigurable hardware devices, such as FPGAs, are increasingly used in embedded systems. To utilize these devices for real-time work loads, scheduling techniques are required that generate predictable task timings. In this paper, we present a partitioning-EDF (earliest deadline first) approach to find such schedules. The FPGA area is partitioned along one dimension into slots. The tasks are partitioned into groups. Then, each group is scheduled to exactly one slot using the EDF rule. We show that the problem of finding an optimal partitioning is related to the well-known 2D level bin-packing problem. We extend a previously reported ILP model to solve our partitioning problem to optimality. By a simulation study we demonstrate that the partitioning-EDF approach is able to find feasible schedules for most task sets with a system utilization of up to 70%. Additionally, we allow a task to be realized in alternative implementations. A simulation study reveals that the scheduling performance increases considerably if three instead of one task variants are considered. Finally, we model and study the impact of the device reconfiguration time on the scheduling performance