Towards Multicore WCET Analysis

AbsInt is the leading provider of commercial tools for static code-level timing analysis. Its aiT Worst-Case Execution Time Analyzer computes tight bounds for the WCET of tasks in embedded real-time systems. However, the results only incorporate the core-local latencies, i.e. interference delays due to other cores in a multicore system are ignored. This paper presents some of the work we have done towards multicore WCET analysis. We look into both static and measurement-based timing analysis for COTS multicore systems

Computing Same Block Relations for Relational Cache Analysis

In contrast to the classical cache analysis of Ferdinand, the relational cache analysis does not rely on precise address information. Instead, it uses same block relations between memory accesses to predict cache hits. The relational data cache analysis can thus also predict cache hits if fully unrolling a loop is not feasible during analysis, for example due to high memory consumption or long computation time. This paper proposes a static analysis based on abstract interpretation which is able to compute same block relations for relational cache analysis

Embedded Program Annotations for WCET Analysis

We present __builtin_ais_annot(), a user-friendly, versatile way to transfer annotations (also known as flow facts) written on the source code level to the machine code level. To do so, we couple two tools often used during the development of safety-critical hard real-time systems, the formally verified C compiler CompCert and the static WCET analyzer aiT. CompCert stores the AIS annotations given via __builtin_ais_annot() in a special section of the ELF binary, which can later be extracted automatically by aiT

TimeWeaver: A Tool for Hybrid Worst-Case Execution Time Analysis

Many embedded control applications have real-time requirements. If the application is safety-relevant, worst-case execution time bounds have to be determined in order to demonstrate deadline adherence. For high-performance multi-core architectures with degraded timing predictability, WCET bounds can be computed by hybrid WCET analysis which combines static analysis with timing measurements. This article focuses on a novel tool for hybrid WCET analysis based on non-intrusive instruction-level real-time tracing

Continuous Non-Intrusive Hybrid WCET Estimation Using Waypoint Graphs

Traditionally, the Worst-Case Execution Time (WCET) of Embedded Software has been estimated using analytical approaches. This is effective, if good models of the processor/System-on-Chip (SoC) architecture exist. Unfortunately, modern high performance SoCs often contain unpredictable and/or undocumented components that influence the timing behaviour. Thus, analytical results for such processors are unrealistically pessimistic. One possible alternative approach seems to be hybrid WCET analysis, where measurement data together with an analytical approach is used to estimate worst-case behaviour. Previously, we demonstrated how continuous evaluation of basic block trace data can be used to produce detailed statistics of basic blocks in embedded software. In the meantime it has become clear that the trace data provided by modern SoCs delivers a different type of information. In this contribution, we show that even under realistic conditions, a meaningful analysis can be conducted with the trace data

EnergyAnalyzer: Using Static WCET Analysis Techniques to Estimate the Energy Consumption of Embedded Applications

This paper presents EnergyAnalyzer, a code-level static analysis tool for estimating the energy consumption of embedded software based on statically predictable hardware events. The tool utilises techniques usually used for worst-case execution time (WCET) analysis together with bespoke energy models developed for two predictable architectures - the ARM Cortex-M0 and the Gaisler LEON3 - to perform energy usage analysis. EnergyAnalyzer has been applied in various use cases, such as selecting candidates for an optimised convolutional neural network, analysing the energy consumption of a camera pill prototype, and analysing the energy consumption of satellite communications software. The tool was developed as part of a larger project called TeamPlay, which aimed to provide a toolchain for developing embedded applications where energy properties are first-class citizens, allowing the developer to reflect directly on these properties at the source code level. The analysis capabilities of EnergyAnalyzer are validated across a large number of benchmarks for the two target architectures and the results show that the statically estimated energy consumption has, with a few exceptions, less than 1% difference compared to the underlying empirical energy models which have been validated on real hardware

Multi-core Interference-Sensitive WCET Analysis Leveraging Runtime Resource Capacity Enforcement

The performance and power efficiency of multi-core processors are attractive features for safety-critical applications, as in avionics. But increased integration and average-case performance optimizations pose challenges when deploying them for such domains. In this paper we propose a novel approach to compute a interference-sensitive Worst-Case Execution Time (isWCET) considering variable accesses delays due to the concurrent use of shared resources in multi-core processors. Thereby we tackle the problem of temporal partitioning as it is required by safety-critical applications. In particular, we introduce additional phases to state-of-the-art timing analysis techniques to analyse an applications resource usage and compute an interference delay. We further complement the offline analysis with a runtime monitoring concept to enforce resource usage guarantees. The concepts are evaluated on Freescale's P4080 multi-core processor in combination with SYSGO's commercial real-time operating system PikeOS and AbsInt's timing analysis framework aiT. We abstract real applications' behavior using a representative task set of the EEMBC Autobench benchmark suite. Our results show a reduction of up to 75% of the multi-core Worst-Case Execution Time (WCET), while implementing full transparency to the temporal and functional behavior of applications, enabling the seamless integration of legacy applications