Leonidas Kosmidis

Measurement-Based Probabilistic Timing Analysis for Multi-path Programs

The rigorous application of static timing analysis requires a large and costly amount of detail knowledge on the hardware and software components of the system. Probabilistic Timing Analysis has potential for reducing the weight of that demand. In this paper, we present a sound measurement-based probabilistic timing analysis technique based on Extreme Value Theory. In all the experiments made as part of this work, the timing bounds determined by our technique were less than 15% pessimistic in comparison with the tightest possible bounds obtainable with any probabilistic timing analysis technique. As a point of interest to industrial users, our technique also requires a comparatively low number of measurement runs of the program under analysis, less than 650 runs were needed for the benchmarks presented in this paper.

PROARTIS: Probabilistically Analyzable Real-Time Systems

Static timing analysis is the state-of-the-art practice of ascertaining the timing behavior of current-generation real-time embedded systems. The adoption of more complex hardware to respond to the increasing demand for computing power in next-generation systems exacerbates some of the limitations of static timing analysis. In particular, the effort of acquiring (1) detailed information on the hardware to develop an accurate model of its execution latency as well as (2) knowledge of the timing behavior of the program in the presence of varying hardware conditions, such as those dependent on the history of previously executed instructions. We call these problems the timing analysis walls. In this vision-statement article, we present probabilistic timing analysis, a novel approach to the analysis of the timing behavior of next-generation real-time embedded systems. We show how probabilistic timing analysis attacks the timing analysis walls; we then illustrate the mathematical foundations on which this method is based and the challenges we face in the effort of efficiently implementing it. We also present experimental evidence that shows how probabilistic timing analysis reduces the extent of knowledge about the execution platform required to produce probabilistically accurate WCET estimations.

A cache design for probabilistically analysable real-time systems

Caches provide significant performance improvements, though their use in real-time industry is low because current WCET analysis tools require detailed knowledge of programs cache accesses to provide tight WCET estimates. Probabilistic Timing Analysis (PTA) has emerged as a solution to reduce the amount of information needed to provide tight WCET estimates, although it imposes new requirements on hardware design. At cache level, so far only fully-associative random-replacement caches have been proven to fulfill the needs of PTA, but they are expensive in size and energy. In this paper we propose a cache design that allows set-associative and direct-mapped caches to be analysed with PTA techniques. In particular we propose a novel parametric random placement suitable for PTA that is proven to have low hardware complexity and energy consumption while providing comparable performance to that of conventional modulo placement.

Measurement-based probabilistic timing analysis: Lessons from an integrated-modular avionics case study

Probabilistic Timing Analysis (PTA) in general and its measurement-based variant called MBPTA in particular can mitigate some of the problems that impair current worst-case execution time (WCET) analysis techniques. MBPTA computes tight WCET bounds expressed as probabilistic exceedance functions, without needing much information on the hardware and software internals of the system. Classic WCET analysis has information needs that may be costly and difficult to satisfy, and their omission increases pessimism. Previous work has shown that MBPTA does well with benchmark programs. Real-world applications however place more demanding requirements on timing analysis than simple benchmarks. It is interesting to see how PTA responds to them. This paper discusses the application of MBPTA to a real avionics system and presents lessons learned in that process.

Probabilistic timing analysis on conventional cache designs

Probabilistic timing analysis (PTA), a promising alternative to traditional worst-case execution time (WCET) analyses, enables pairing time bounds (named probabilistic WCET or pWCET) with an exceedance probability (e.g., 10−16), resulting in far tighter bounds than conventional analyses. However, the applicability of PTA has been limited because of its dependence on relatively exotic hardware: fully-associative caches using random replacement. This paper extends the applicability of PTA to conventional cache designs via a software-only approach. We show that, by using a combination of compiler techniques and runtime system support to randomise the memory layout of both code and data, conventional caches behave as fully-associative ones with random replacement.

Bus designs for time-probabilistic multicore processors

Probabilistic Timing Analysis (PTA) reduces the amount of information needed to provide tight WCET estimates in real-time systems with respect to classic timing analysis. PTA imposes new requirements on hardware design that have been shown implementable for single-core architectures. However, no support has been proposed for multicores so far. In this paper, we propose several probabilistically-analysable bus designs for multicore processors ranging from 4 cores connected with a single bus, to 16 cores deploying a hierarchical bus design. We derive analytical models of the probabilistic timing behaviour for the different bus designs, show their suitability for PTA and evaluate their hardware cost. Our results show that the proposed bus designs (i) fulfil PTA requirements, (ii) allow deriving WCET estimates with the same cost and complexity as in single-core processors, and (iii) provide higher guaranteed performance than single-core processors, 3.4x and 6.6x on average for an 8-core and a 16-core setup respectively.

Multi-level Unified Caches for Probabilistically Time Analysable Real-Time Systems

Caches are key resources in high-end processor architectures to increase performance. In fact, most high-performance processors come equipped with a multi-level cache hierarchy. In terms of guaranteed performance, however, cache hierarchies severely challenge the computation of tight worst-case execution time (WCET) estimates. On the one hand, the analysis of the timing behaviour of a single level of cache is already challenging, particularly for data accesses. On the other hand, unifying data and instructions in each level, makes the problem of cache analysis significantly more complex requiring tracking simultaneously data and instruction accesses to cache. In this paper we prove that multi-level cache hierarchies can be used in the context of Probabilistic Timing Analysis and tight WCET estimates can be obtained. Our detailed analysis (1) covers unified data and instruction caches, (2) covers different cache-write policies (write-through and write back), write allocation policies (write-allocate and non-write-allocate) and several inclusion mechanisms (inclusive, non-inclusive and exclusive caches), and (3) scales to an arbitrary number of cache levels. Our results show that the probabilistic WCET (pWCET) estimates provided by our analysis technique effectively benefit from having multi-level caches. For a two-level cache configuration and for EEMBC benchmarks, pWCET reductions are 55% on average (and up to 90%) with respect to a processor with a single level of cache.

Timing analysis of an avionics case study on complex hardware/software platforms

Probabilistic Timing Analysis (PTA) in general and its measurement-based variant called MBPTA in particular have been shown to facilitate the estimation of the worst-case execution time (WCET). MBPTA relies on specific hardware and software support to randomise and/or upper bound a number of sources of execution time variation to drastically reduce the need for user-provided information, thus replacing uncertainty by probabilities. MBPTA has been proven effective for specific single-core processor designs. However, particular hardware features and multicores in general challenge MBPTA application in industrial-quality developments. While solutions to those challenges have been proven on benchmarks, they have not been proven yet on real-world applications, whose timing analysis is far more challenging than that of simple benchmarks. This paper discusses the application of MBPTA to a real avionics system in the context of (1) software-only single-core solutions and (2) hardware-only multicore solutions with an ARINC 653 operating system.

DTM: Degraded Test Mode for Fault-Aware Probabilistic Timing Analysis

Existing timing analysis techniques to derive Worst-Case Execution Time (WCET) estimates assume that hardware in the target platform (e.g., the CPU) is fault-free. Given the performance requirements increase in current Critical Real-Time Embedded Systems (CRTES), the use of high-performance features and smaller transistors in current and future hardware becomes a must. The use of smaller transistors helps providing more performance while maintaining low energy budgets, however, hardware fault rates increase noticeably, affecting the temporal behaviour of the system in general, and WCET in particular. In this paper, we reconcile these two emergent needs of CRTES, namely, tight (and trustworthy) WCET estimates and the use of hardware implemented with smaller transistors. To that end we propose the Degraded Test Mode (DTM) that, in combination with fault-tolerant hardware designs and probabilistic timing analysis techniques, (i) enables the computation of tight and trustworthy WCET estimates in the presence of faults, (ii) provides graceful average and worst-case performance degradation due to faults, and (iii) requires modifications neither in WCET analysis tools nor in applications. Our results show that DTM allows accounting for the effect of faults at analysis time with low impact in WCET estimates and negligible hardware modifications.

PUB: Path Upper-Bounding for Measurement-Based Probabilistic Timing Analysis

Measurement-Based Probabilistic Timing Analysis (MBPTA) responds to the challenge of analysing the timing behaviour of real-time software running on hardware deploying high-performance features (e.g., data caches). MBPTA provides a WCET estimate that upper-bounds the execution time of the set of paths exercised with the data input vectors provided by the user. However, in several scenarios, the user is unaware of the input vector leading to the worst-case path. In this paper we present PUB, a new method that makes the WCET estimates obtained with MBPTA a trustworthy upper-bound of the probabilistic execution time of all paths in the program, even when the user-provided input vectors do not exercise the worst-case path. This significantly reduces the requirements imposed on the user to apply MBPTA. For Malardarlen and EEMBC respectively, PUB provides WCET estimates 5% and 11% higher than the WCET estimates computed with MBPTA.