Worst-case Execution Time Of Applications Research Articles

Multicore-Aware Code Co-Positioning to Reduce WCET on Dual-Core Processors with Shared Instruction Caches

For real-time systems it is important to obtain the accurate worst-case execution time (WCET). Furthermore, how to improve the WCET of applications that run on multicore processors is both significant and challenging as the WCET can be largely affected by the possible inter-core interferences in shared resources such as the shared L2 cache. In order to solve this problem, we propose an innovative approach that adopts a code positioning method to reduce the inter-core L2 cache interferences between the different real-time threads that adaptively run in a multi-core processor by using different strategies. The worst-case-oriented strategy is designed to decrease the worst-case WCET among these threads to as low as possible. The other two strategies aim at reducing the WCET of each thread to almost equal percentage or amount. Our experiments indicate that the proposed multicore-aware code positioning approaches, not only improve the worstcase performance of the real-time threads but also make good tradeoffs between efficiency and fairness for threads that run on multicore platforms.

Instruction cache locking for multi-task real-time embedded systems

In a multi-task embedded system, a cache is shared by different tasks, which increases the complexity of cache management and the unpredictability of cache behavior. This unpredictability in turn brings an overestimation of application's worst-case execution time (WCET) and worst-case CPU utilization (WCU) which are two of the most important criteria for real-time embedded systems. Modern processors often provide cache locking capability, which can be applied statically and dynamically to manage cache in a predictable manner. The selection of instructions to be locked in the instruction cache (I-Cache) has dramatic influence on the system performance. This paper focuses on applying cache locking techniques to the shared I-Cache to minimize WCU for multi-task embedded systems. We analyze and compare three different strategies to perform I-Cache locking: static locking, semi-dynamic locking, and dynamic locking. Different algorithms are proposed utilizing the foreknown information of embedded applications. Experimental results show that the proposed algorithms can reduce WCU compared to previous techniques.