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Control applications are often implemented on highly cost-sensitive and resource-constrained embedded platforms, such as microcontrollers with a small on-chip memory. Typically, control algorithms are designed using model-based approaches, where the details of the implementation platform are completely ignored. As a result, optimizations that integrate platform-level characteristics into the control algorithms design are largely missing. With the emergence of cyber-physical systems (CPS)-oriented thinking, there has lately been a strong interest in co-design of control algorithms and their implementation platforms, leading to work on networked control systems and computation-aware control algorithms design. However, there has so far been no work on integrating the characteristics of a memory architecture into the design of control algorithms. In this paper we, for the first time, show that accounting for the impact of on-chip memory (or cache) reuse on the performance of control applications motivates new techniques for control algorithms design. This leads to significant improvement in quality of control for given resource availability, or more efficient implementations of embedded control applications. We believe that this paper opens up a variety of possibilities for memory-related optimizations of embedded control systems, that will be pursued by researchers working on computer-aided design for CPS. [ABSTRACT FROM PUBLISHER]

The performance of most embedded systems is critically dependent on the average memory access latency. Improving the cache hit rate can have significant positive impact on the performance of an application. Modern embedded processors often feature cache locking mechanisms that allow memory blocks to be locked in the cache under software control. Cache locking was primarily designed to offer timing predictability for hard real-time applications. Hence, prior techniques focus on employing cache locking to improve the worst-case execution time. However, cache locking can be quite effective in improving the average-case execution time of general embedded applications as well. In this paper, we explore static instruction cache locking to improve the average-case program performance. We introduce temporal reuse profile (TRP) to accurately and efficiently model the cost and benefit of locking memory blocks in the cache. We consider two locking mechanisms, line locking and way locking. For each locking mechanism, we propose a branch-and-bound algorithm and a heuristic approach that use the TRP to determine the most beneficial memory blocks to be locked in the cache. Experimental results show that the heuristic approach achieves close to the results of branch-and-bound algorithm and can improve the performance by 12% on average for 4 KB cache across a suite of real-world benchmarks. Moreover, our heuristic provides significant improvement compared to the state-of-the-art locking algorithm both in terms of performance and efficiency. [ABSTRACT FROM PUBLISHER]