64 research outputs found

    Design and Implementation of a Time Predictable Processor: Evaluation With a Space Case Study

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    Embedded real-time systems like those found in automotive, rail and aerospace, steadily require higher levels of guaranteed computing performance (and hence time predictability) motivated by the increasing number of functionalities provided by software. However, high-performance processor design is driven by the average-performance needs of mainstream market. To make things worse, changing those designs is hard since the embedded real-time market is comparatively a small market. A path to address this mismatch is designing low-complexity hardware features that favor time predictability and can be enabled/disabled not to affect average performance when performance guarantees are not required. In this line, we present the lessons learned designing and implementing LEOPARD, a four-core processor facilitating measurement-based timing analysis (widely used in most domains). LEOPARD has been designed adding low-overhead hardware mechanisms to a LEON3 processor baseline that allow capturing the impact of jittery resources (i.e. with variable latency) in the measurements performed at analysis time. In particular, at core level we handle the jitter of caches, TLBs and variable-latency floating point units; and at the chip level, we deal with contention so that time-composable timing guarantees can be obtained. The result of our applied study with a Space application shows how per-resource jitter is controlled facilitating the computation of high-quality WCET estimates

    Dynamic software randomisation: Lessons learnec from an aerospace case study

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    Timing Validation and Verification (V&V) is an important step in real-time system design, in which a system's timing behaviour is assessed via Worst Case Execution Time (WCET) estimation and scheduling analysis. For WCET estimation, measurement-based timing analysis (MBTA) techniques are widely-used and well-established in industrial environments. However, the advent of complex processors makes it more difficult for the user to provide evidence that the software is tested under stress conditions representative of those at system operation. Measurement-Based Probabilistic Timing Analysis (MBPTA) is a variant of MBTA followed by the PROXIMA European Project that facilitates formulating this representativeness argument. MBPTA requires certain properties to be applicable, which can be obtained by selectively injecting randomisation in platform's timing behaviour via hardware or software means. In this paper, we assess the effectiveness of the PROXIMA's dynamic software randomisation (DSR) with a space industrial case study executed on a real unmodified hardware platform and an industrial operating system. We present the challenges faced in its development, in order to achieve MBPTA compliance and the lessons learned from this process. Our results, obtained using a commercial timing analysis tool, indicate that DSR does not impact the average performance of the application, while it enables the use of MBPTA. This results in tighter pWCET estimates compared to current industrial practice.The research leading to these results has received funding from the European Community’s FP7 [FP7/2007-2013] under the PROXIMA Project (www.proxima-project.eu), grant agreement no 611085. This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717.Peer ReviewedPostprint (author's final draft

    Diversity of cacao trees in Waslala, Nicaragua: Associations between genotype spectra, product quality and yield potential

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    The sensory quality and the contents of quality-determining chemical compounds in unfermented and fermented cocoa from 100 cacao trees (individual genotypes) representing groups of nine genotype spectra (GG), grown at smallholder plantings in the municipality of Waslala, Nicaragua, were evaluated for two successive harvest periods. Cocoa samples were fermented using a technique mimicking recommended on-farm practices. The sensory cocoa quality was assessed by experienced tasters, and seven major chemical taste compounds were quantified by near infrared spectrometry (NIRS). The association of the nine, partially admixed, genotype spectra with the analytical and sensory quality parameters was tested. The individual parameters were analyzed as a function of the factors GG and harvest (including the date of fermentation), individual trees within a single GG were used as replications. In fermented cocoa, significant GG-specific differences were observed for methylxanthines, theobromine-to-caffeine (T/C) ratio, total fat, procyanidin B5 and epicatechin, as well as the sensory attributes global score, astringency, and dry fruit aroma, but differences related to harvest were also apparent. The potential cocoa yield was also highly determined by the individual GG, although there was significant tree-to-tree variation within every single GG. Non-fermented samples showed large harvest-to-harvest variation of their chemical composition, while differences between GG were insignificant. These results suggest that selection by the genetic background, represented here by groups of partially admixed genotype spectra, would be a useful strategy toward enhancing quality and yield of cocoa in Nicaragua. Selection by the GG within the local, genetically segregating populations of seedpropagated cacao, followed by clonal propagation of best-performing individuals of the selected GG could be a viable alternative to traditional propagation of cacao by seed from open pollination. Fast and gentle air-drying of the fermented beans and their permanent dry storage were an efficient and comparatively easy precondition for high cocoa quality. (Résumé d'auteur

    Improving Measurement-Based Timing Analysis through Randomisation and Probabilistic Analysis

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    The use of increasingly complex hardware and software platforms in response to the ever rising performance demands of modern real-time systems complicates the verification and validation of their timing behaviour, which form a time-and-effort-intensive step of system qualification or certification. In this paper we relate the current state of practice in measurement-based timing analysis, the predominant choice for industrial developers, to the proceedings of the PROXIMA project in that very field. We recall the difficulties that the shift towards more complex computing platforms causes in that regard. Then we discuss the probabilistic approach proposed by PROXIMA to overcome some of those limitations. We present the main principles behind the PROXIMA approach as well as the changes it requires at hardware or software level underneath the application. We also present the current status of the project against its overall goals, and highlight some of the principal confidence-building results achieved so far

    Genetic prediction of complex traits: integrating infinitesimal and marked genetic effects

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    Genetic prediction for complex traits is usually based on models including individual (infinitesimal) or marker effects. Here, we concentrate on models including both the individual and the marker effects. In particular, we develop a ''Mendelian segregation'' model combining infinitesimal effects for base individuals and realized Mendelian sampling in descendants described by the available DNA data. The model is illustrated with an example and the analyses of a public simulated data file. Further, the potential contribution of such models is assessed by simulation. Accuracy, measured as the correlation between true (simulated) and predicted genetic values, was similar for all models compared under different genetic backgrounds. As expected, the segregation model is worthwhile when markers capture a low fraction of total genetic variance. (Résumé d'auteur

    J Clin Immunol

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    We report a longitudinal analysis of the immune response associated with a fatal case of COVID-19 in Europe. This patient exhibited a rapid evolution towards multiorgan failure. SARS-CoV-2 was detected in multiple nasopharyngeal, blood, and pleural samples, despite antiviral and immunomodulator treatment. Clinical evolution in the blood was marked by an increase (2–3-fold) in differentiated effector T cells expressing exhaustion (PD-1) and senescence (CD57) markers, an expansion of antibody-secreting cells, a 15-fold increase in γδ T cell and proliferating NK-cell populations, and the total disappearance of monocytes, suggesting lung trafficking. In the serum, waves of a pro-inflammatory cytokine storm, Th1 and Th2 activation, and markers of T cell exhaustion, apoptosis, cell cytotoxicity, and endothelial activation were observed until the fatal outcome. This case underscores the need for well-designed studies to investigate complementary approaches to control viral replication, the source of the hyperinflammatory status, and immunomodulation to target the pathophysiological response. The investigation was conducted as part of an overall French clinical cohort assessing patients with COVID-19 and registered in clinicaltrials.gov under the following number: NCT04262921
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