Abstract. In the last few years, the traditional ways to keep the increase of hardware performance to the rate predicted by the Moore's Law have vanished. When uni-cores were the norm, hardware design was decoupled from the software stack thanks to a well defined Instruction Set Architecture (ISA). This simple interface allowed developing applications without worrying too much about the underlying hardware, while hardware designers were able to aggressively exploit instructionlevel parallelism (ILP) in superscalar processors. Current multi-cores are designed as simple symmetric multiprocessors (SMP) on a chip. However, we believe that this is not enough to overcome all the problems that multi-cores face. The runtime of the parallel application has to drive the design of future multi-cores to overcome the restrictions in terms of power, memory, programmability and resilience that multi-cores have. In the paper, we introduce a first approach towards a Runtime-Aware Architecture (RAA), a massively parallel architecture designed from the runtime's perspective.
Objectives Studies on coronavirus disease 2019 (COVID-19) have mainly focused on hospitalized patients or those with severe disease. We aim to assess the clinical characteristics, outcomes and factors associated with hospital admission or death in adult outpatients with COVID-19. Methods This is a prospective cohort of outpatients with suspected or confirmed COVID-19, registered in Covidom telesurveillance solution for home monitoring of patients with COVID-19 in the Greater Paris area, from March to August 2020. The primary outcome was clinical worsening, defined as hospitalization or death within 1 month after symptom onset. Results Among 43,103 patients, mean age was 42.9 years (SD=14.3); 93.0% (n=40,081) of patients were < 65 years old and 61.9% (n=26,688) were women. Of these 43,103 patients, 67.5% (n=29,104) completed a medical questionnaire on comorbidities and symptoms. The main reported comorbidities were asthma (12.8%; n=3,685), hypertension (12.3%; n=3,546) and diabetes (4.8%; n=1,385). A small proportion of all eligible patients (4.1% [95% CI: 3.9–4.2]; 1,751/43,103) experienced clinical worsening. The rate of hospitalisation was 4.0% (95% CI: 3.8–4.2; n=1,728) and 0.1% (95% CI: 0.1–0.2; n=64) died. Factors associated with clinical worsening were male sex, older age, obesity and comorbidities such as chronic renal disease or cancer under treatment. Probability of worsening was reduced with anosmia/ageusia. Conclusions Clinical worsening was rare among outpatients. Male sex, older age and comorbidities such as chronic renal disease, active cancers or obesity were independently associated with clinical worsening. However, our cohort may include patients younger and healthier than the general population.
This paper presents a method to protect iterative solvers from Detected and Uncorrected Errors (DUE) relying on error detection techniques already available in commodity hardware. Detection operates at the memory page level, which enables the use of simple algorithmic redundancies to correct errors. Such redundancies would be inapplicable under coarse grain error detection, but become very powerful when the hardware is able to precisely detect errors.\ud Relations straightforwardly extracted from the solver allow to recover lost data exactly. This method is free of the overheads of backwards recoveries like checkpointing, and does not compromise mathematical convergence properties of the solver as restarting would do. We apply this recovery to three widely used Krylov subspace methods, CG, GMRES and BiCGStab, and their preconditioned versions.\ud We implement our resilience techniques on CG considering scenarios from small (8 cores) to large (1024 cores) scales, and demonstrate very low overheads compared to state-of-the-art solutions. We deploy our recovery techniques either by overlapping them with algorithmic computations or by forcing them to be in the critical path of the application. A trade-off exists between both approaches depending on the error rate the solver is suffering. Under realistic error rates, overlapping decreases overheads from 5.37% down to 3.59% for a non-preconditioned CG on 8 cores.This work has been partially supported by the European Research Council under the European Union's 7th FP, ERC Advanced Grant 321253, and by the Spanish Ministry of Science and Innovation under grant TIN2012-34557. L. Jaulmes has been partially supported by the Spanish Ministry of Education, Culture and Sports under grant FPU2013/06982.\ud M. Moreto has been partially supported by the Spanish Ministry of Economy and Competitiveness under Juan de la\ud Cierva postdoctoral fellowship JCI-2012-15047. M. Casas\ud has been partially supported by the Secretary for Universities and Research of the Ministry of Economy and Knowledge of the Government of Catalonia and the Co-fund programme of the Marie Curie Actions of the European Union's 7th FP (contract 2013 BP\ud B 00243).Peer ReviewedPostprint (author's final draft
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.