Dynamic instruction cache locking in hard real-time systems

In real-time systems, cache memory poses challenge to improve both predictability and performance because of its adaptive and dynamic behavior. Recent studies indicate that for application-specific embedded systems, static cache-locking helps determining the worst case execution time (WCET) and cache-related preemption delay. In this work, we propose a static instruction cachelocking algorithm that makes the real-time embedded system more predictable by locking the blocks that might cause more cache misses. We obtain CPU utilization for both static cache analysis (no cache-locking) and static cache-locking using Heptane. Experimental results show that our cache-locking algorithm may improve both predictability and performance of real-time systems.

Proceedings of the Tenth International Symposium on Code Generation and Optimization - CHO '12, 2012

In the past decades, embedded system designers moved from simple, predictable system designs towards complex systems equipped with caches. This step was necessary in order to bridge the increasingly growing gap between processor and memory system performance. Static analysis techniques had to be developed to allow the estimation of the cache behavior and an upper bound of the execution time of a program. This bound is called worst-case execution time (WCET ). Its knowledge is crucial to verify whether hard real-time systems satisfy their timing constraints, and the WCET is a key parameter for the design of embedded systems.

Trustable Worst-Case Execution-Time (WCET) bounds are a necessary component for the construction and verification of hard real-time computer systems. Deriving such bounds for contemporary hardware/software systems is a complex task. The single-path conversion overcomes this difficulty by transforming all unpredictable branch alternatives in the code to a sequential code structure with a single execution trace. However, the simpler code structure and analysis of single-path code comes at the cost of a longer execution time. In this paper we address the problem of the execution performance of single-path code. We present a new cache orga- nization that utilizes the principle of locality of single-path code to reduce cache miss latency and cache miss rate. The proposed cache memory architecture combines cache prefetching and cache locking, so that the prefetcher capitalizes on spatial locality while the locker makes use of temporal locality. The demonstration section shows how these two techniques can complement each other.

IEEE Transactions on Software Engineering, 2001

ÐCache memory is used in almost all computer systems today to bridge the ever increasing speed gap between the processor and main memory. However, its use in multitasking computer systems introduces additional preemption delay due to the reloading of memory blocks that are replaced during preemption. This cache-related preemption delay poses a serious problem in realtime computing systems where predictability is of utmost importance. In this paper, we propose an enhanced technique for analyzing and thus bounding the cache-related preemption delay in fixed-priority preemptive scheduling focusing on instruction caching. The proposed technique improves upon previous techniques in two important ways. First, the technique takes into account the relationship between a preempted task and the set of tasks that execute during the preemption when calculating the cache-related preemption delay. Second, the technique considers the phasing of tasks to eliminate many infeasible task interactions. These two features are expressed as constraints of a linear programming problem whose solution gives a guaranteed upper bound on the cache-related preemption delay. This paper also compares the proposed technique with previous techniques using randomly generated task sets. The results show that the improvement on the worst-case response time prediction by the proposed technique over previous techniques ranges between 5 percent and 18 percent depending on the cache refill time when the task set utilization is 0.6. The results also show that as the cache refill time increases, the improvement increases, which indicates that accurate prediction of cache-related preemption delay by the proposed technique becomes increasingly important if the current trend of widening speed gap between the processor and main memory continues.

2009

While caches are essential to reduce execution time and power consumption, they complicate the estimation of the Worst-Case Execution Time (WCET), crucial for many Real-Time Systems (RTS). Most research on static worst-case cache behavior prediction has focused on hard RTS, which need complete information on the access patterns and addresses of the data to guarantee the predicted WCET is a safe upper bound of any execution time. Access patterns are available in those codes that have a steady state of access patterns after the first iteration of a loop (in the following regular codes), however, the addresses of the data are not always known at compile time for many reasons: stack variables, dynamically allocated memory, modules compiled separately, etc. Even when available, their usefulness to predict cache behavior in systems with virtual memory decreases in the presence of physically-indexed caches. In this paper we present a model that predicts a reasonable bound of the worst-case behavior of data caches during the execution of regular codes without information on the base address of the data structures. In 99.7% of our tests the number of misses performed below the boundary predicted by the model. This turns the model into a valuable tool, particularly for non-RTS and soft RTS, which tolerate a percentage of the runs exceeding their deadlines.

PLOS ONE

One of the key challenges in real-time systems is the analysis of the memory hierarchy. Many Worst-Case Execution Time (WCET) analysis methods supporting an instruction cache are based on iterative or convergence algorithms, which are rather slow. Our goal in this paper is to reduce the WCET analysis time on systems with a simple lockable instruction cache, focusing on the Lock-MS method. First, we propose an algorithm to obtain a structure-based representation of the Control Flow Graph (CFG). It organizes the whole WCET problem as nested subproblems, which takes advantage of common branch-and-bound algorithms of Integer Linear Programming (ILP) solvers. Second, we add support for multiple locking points per task, each one with specific cache contents, instead of a given locked content for the whole task execution. Locking points are set heuristically before outer loops. Such simple heuristics adds no complexity, and reduces the WCET by taking profit of the temporal reuse found in loops. Since loops can be processed as isolated regions, the optimal contents to lock into cache for each region can be obtained, and the WCET analysis time is further reduced. With these two improvements, our WCET analysis is around 10 times faster than other approaches. Also, our results show that the WCET is reduced, and the hit ratio achieved for the lockable instruction cache is similar to that of a real execution with an LRU instruction cache. Finally, we analyze the WCET sensitivity to compiler optimization, showing for each benchmark the right choices and pointing out that O0 is always the worst option.

Journal of Systems Architecture, 2011

In multitasking real-time systems it is required to compute the WCET of each task and also the effects of interferences between tasks in the worst case. This is very complex with variable latency hardware, such as instruction cache memories, or, to a lesser extent, the line buffers usually found in the fetch path of commercial processors. Some methods disable cache replacement so that it is easier to model the cache behavior. The difficulty in these cache-locking methods lies in obtaining a good selection of the memory lines to be locked into cache. In this paper, we propose an ILP-based method to select the best lines to be loaded and locked into the instruction cache at each context switch (dynamic locking), taking into account both intra-task and inter-task interferences, and we compare it with static locking. Our results show that, without cache, the spatial locality captured by a line buffer doubles the performance of the processor. When adding a lockable instruction cache, dynamic locking systems are schedulable with a cache size between 12.5% and 50% of the cache size required by static locking. Additionally, the computation time of our analysis method is not dependent on the number of possible paths in the task. This allows us to analyze large codes in a relatively short time (100 KB with 10 65 paths in less than 3 min).