Improving and Estimating the Precision of Bounds on the Worst-Case Latency of Task Chains

Special Issue of the EMSOFT 2018 International ConferenceInternational audienceOne major issue that hinders the use of performance analysis in industrial design processes is the pessimism inherent to any analysis technique that applies to realistic system models. Indeed, such analyses may conservatively declare unschedulable systems that will in fact never miss any deadlines. We advocate the need to compute not only tight upper bounds on worst-case behaviors, but also tight lower bounds. As a first step, we focus on uniprocessor systems executing a set of sporadic or periodic hard real-time task chains. Each task has its own priority, and the chains are scheduled according to the fixed-priority preemptive scheduling policy. Computing the worst-case end-to-end latency (WCEL) of each chain is complex because of the intricate relationship between the task priorities. Compared to the state of the art, our analysis provides upper bounds on the WCEL in the more general case of asynchro-nous task chains, and also provides lower bounds on the WCEL both for synchronous and asynchronous chains. Our computed lower bounds correspond to actual system executions exhibiting a behavior that is as close to the worst case as possible, while all other approaches rely on simulations. Extensive experiments show the relevance of lower bounds on the worst-case behavior for the industrial design of real-time embedded systems. CCS CONCEPTS • Computer systems organization → Embedded systems; KEYWORDS Worst-case end to end latency, Latency analysis, Task chains ACM Reference format

Demo Abstract: Bounding Deadline Misses for Weakly-Hard Real-Time Systems Designed in CAPELLA

International audienceReal-time systems with functional dependencies between tasks often require guarantees on end-to-end delays. For many of these systems, end-to-end deadline misses are accepted if one can limit their frequency. Such systems are called weakly-hard. Recent work has shown that typical worst-case analysis (TWCA) can compute an upper bound on the number of potential deadline misses in a sequence of activations of a task chain. In a joint collaboration between Thales and TU Braunschweig, the use of TWCA to limit the number of deadline misses in an aerial video tracking (AVT) system was evaluated. The AVT case-study, the complete automated model-based tool chain from the design environment to the timing verification using TWCA, as well as the results of the evaluation will be presented in the demonstration. The tool chain involves four tools: the design modeling tool CAPELLA extended by a performance viewpoint which allows annotating the design model with timing properties needed to perform TWCA, the pivot model TEMPO which handles mismatches between the semantics of the design model and the semantics of the model used in TWCA, the scheduling analysis tool pyCPA that performs TWCA and finally the graphical tool TimingGraphics used to visualize the TWCA results. To show the pertinence of the use of TWCA, we will also compare in the demonstration the obtained results with those obtained using worst-case analysis and simulation

RT-simex: retro-analysis of execution traces

International audienceThis presentation demonstrates the early results from the French ANR project RT-Simex. RT-Simex proposes a set of tools to analyze timing of parallel embedded code and trace the simulation results back to the initial models from which the code was generated. The whole tool-set relies on standard formats (uml marte, Open Trace Format) to ensure a perennial use. This is achieved through the polychronous logical time model of marte

Time4Sys – Integrating Timing Verification in your Engineering Practices

International audienc

Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Risk for late-onset Alzheimer’s disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer’s or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer’s disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10−7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education

Author Correction: Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (Nature Genetics, (2019), 51, 3, (414-430), 10.1038/s41588-019-0358-2)

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Author Correction: Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (Nature Genetics, (2019), 51, 3, (414-430), 10.1038/s41588-019-0358-2)

An amendment to this paper has been published and can be accessed via a link at the top of the paper