Extending Embedded Computing Scheduling Algorithms for Reconfigurable Computing Systems

Current work on automatic task partitioning and scheduling for reconfigurable computing (RC) systems strictly addresses the FPGA hardware, and does not take advantage of the synergy between the microprocessor and the FPGA. Efforts on partitioning between muP and the FPGA are a manual and laborious effort, as a formal methodology for automatic hardware-software partitioning has not been established. Related fields such as heterogeneous computing (HC) and embedded computing (EC) have an extensive body of work for scheduling for heterogeneous processors. Unlike the HC scheduling algorithms, the EC algorithms take into account the differences in computational capabilities of each processing element. In this work, we adapt EC scheduling algorithms for RC systems, and show how simply adapting the algorithms alone is not sufficient to take advantage of the reconfigurable hardware. We introduce new heuristic algorithms based on EC scheduling algorithms and show that they provide up to an order of magnitude improvement in scheduling and execution times.