One of the primary sources of unpredictability in modern multi-core embedded systems is contention over shared memory resources, such as caches, interconnects, and DRAM. Despite significant achievements in the design and analysis of multi-core systems, there is a need for a theoretical framework that can be used to reason on the worst-case behavior of real-time workload when both processors and memory resources are subject to scheduling decisions. In this paper, we focus our attention on dynamic allocation of main memory bandwidth. In particular, we study how to determine the worst-case response time of tasks spanning through a sequence of time intervals, each with a different bandwidth-to-core assignment. We show that the response time computation can be reduced to a maximization problem over assignment of memory requests to different time intervals, and we provide an efficient way to solve such problem. As a case study, we then demonstrate how our proposed analysis can be used to improve the schedulability of Integrated Modular Avionics systems in the presence of memory-intensive workload.

Airbus is investigating COTS multicore platforms for safety-critical avionics applications, pursuing helicopter-style autonomous and electric aircraft. These aircraft need to be ultra-lightweight for future mobility in the urban city landscape. As a step towards certification, Airbus identified the need for new methods that preserve the ARINC 653 single core schedule of a Helicopter Terrain Awareness and Warning System (HTAWS) application while scheduling additional safety-critical partitions on the other cores. As some partitions in the HTAWS application are memory-intensive, static memory bandwidth throttling may lead to slow down of such partitions or provide only little remaining bandwidth to the other cores. Thus, there is a need for dynamic memory bandwidth isolation. This poses new challenges for scheduling, as execution times and scheduling become interdependent: scheduling requires execution times as input, which depends on memory latencies and contention from memory accesses of other cores - which are determined by scheduling. Furthermore, execution times depend on memory access patterns. In this paper, we propose a method to solve this problem for slot-based time-triggered systems without requiring application source-code modifications using a number of dynamic memory bandwidth levels. It is NoC and DRAM controller contention-aware and based on the existing interference-sensitive WCET computation and the memory bandwidth throttling mechanism. It constructs schedule tables by assigning partitions and dynamic memory bandwidth to each slot on each core, considering worst case memory access patterns. Then at runtime, two servers - for processing time and memory bandwidth - run on each core, jointly controlling the contention between the cores and the amount of memory accesses per slot. As a proof-of-concept, we use a constraint solver to construct tables. Experiments on the P4080 COTS multicore platform, using a research OS from Airbus and EEMBC benchmarks, demonstrate that our proposed method enables preserving existing schedules on a core while scheduling additional safety-critical partitions on other cores, and meets dynamic memory bandwidth isolation requirements.

In this work, we present an initial step towards enabling TT scheduling on a real COTS multicore platform P4080. It takes into account inter-core interferences in the on-chip network and the memory sub-system. We propose an approach comprising a runtime mechanism and an offline phase. For the runtime mechanism, we propose two servers running on each core-processing time server and memory access server implemented using built-in hardware monitors. Jointly, the two servers on each core, enforce slot-level offline computed server budget reservations, thereby limiting the maximum inter-core interferences introduced and experienced by each task considering different inter-core interference latencies. In the offline phase, we propose a procedure that can be used by any offline scheduler to compute the bound on variability in execution time of each task while allowing different slot-level memory access server budget reservations. We also did a preliminary bare-metal implementation of our proposed runtime mechanism on a real COTS multicore platform P4080. Overall, our proposed method facilitates integration of COTS multicore platforms in TT systems, while maintaining features of TT architecture like slot-level determinism, clock synchronization, etc.