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A formal approach to the WCRT analysis of multicore systems with memory contention under phase-structured task sets. Real-time systemshttp://dx.doi.org/10.1007/s11241-014-9211-y Access to the published version may require subscription. N.B. When citing this work, cite the original published paper. Abstract Multicore technology has the potential for drastically increasing productivity of embedded real-time computing. However, joint use of hardware, e.g., caches, memory banks and on-chip buses makes the integration of multiple real-time applications into a single system difficult: resource accesses are exclusive and need to be sequenced. Moreover, resource access schemes of modern off-the-shelf multicore chips are commonly optimized for the average-case, rather than being timing predictable. Real-time analysis for such architectures is complex, as execution times depend on the deployed hardware, as well as on the software executing on other cores. This will ask for significant abstractions in the timing analysis, where the resulting pessimism will lead to over-provisioned system designs and a lowered productivity as the number of applications to be put together into a single architecture needs to be decreased. In response to this, (a) we present a formal approach for bounding the worst-case response time of concurrently executing real-time tasks under resource contention and almost arbitrarily complex resource arbitration policies, with a focus on main memory as shared resource, (b) we present a simulation framework which allows for detailed modeling and empirical evaluation of modern multicore platforms and applications running on top of them, and (c) we present experiments to demonstrate the advantages and disadvantages of the presented methodologies and compare their accuracy. For limiting non-determinism inherent to the occurrence of cache misses, we particularly take advantage from the PRedictable Execution Model (PREM) as discussed in recent works.

As multi-core systems are becoming more popular in real-time embedded systems, strict timing requirements for accessing shared resources must be met. In particular, a detailed latency analysis for Double Data Rate Dynamic RAM (DDR DRAM) is highly desirable. Several researchers have proposed predictable memory controllers to provide guaranteed memory access latency. However, the performance of such controllers sharply decreases as DDR devices become faster and the width of memory buses is increased. High-performance Commercial-Off-The-Shelf (COTS) memory controllers in general-purpose systems employ open row policy to improve average case access latencies and memory throughput, but the use of such policy is not compatible with existing real-time controllers. In this article, we present a new memory controller design together with a novel, composable worst case analysis for DDR DRAM that provides improved latency bounds compared to existing works by explicitly modeling the DRAM state. In particular, our approach scales better with increasing memory speed by predictably taking advantage of shorter latency for access to open DRAM rows. Furthermore, it can be applied to multi-rank devices, which allow for increased access parallelism. We evaluate our approach based on worst case analysis bounds and simulation results, using both synthetic tasks and a set of realistic benchmarks. In particular, benchmark evaluations show up to 45% improvement in worst case task execution time compared to a competing predictable memory controller for a system with 16 requestors and one rank.