Placement of Chains of Real-Time Tasks on Heterogeneous Platforms under EDF Scheduling

When designing a real-time system, application architects are called to settle many non-trivial decisions that may severely influence the system's performance. With modern hardware platforms always being more and more complex and equipped with heterogeneous processor cores or even hardware accelerators such as TPUs, FPGAs, or GPUs, the complexities to be faced by application architects are exacerbated. Therefore, they are called to wisely allocate the computational resources provided by the hardware platform to application tasks in such a way to meet timing requirements and optimize other goals such as energy consumption. This paper proposes a mixed-integer linear programming formulation (MILP) to solve the task-to-heterogeneous-cores allocation problem while guaranteeing the schedulability of a real-time application running on the platform under partitioned Earliest Deadline First (EDF) scheduling. A new method to derive approximate worst-case response-time bounds is also presented and leveraged to setup the MILP formu-lation, which allows computing and minimizing the end-to-end latency of processing chains and considers energy requirements. The approach is evaluated on a task set based on the WATERS 2019 Industrial Challenge proposed by Bosch.