76 research outputs found

    Directions in parallel programming: HPF, shared virtual memory and object parallelism in pC++

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    Fortran and C++ are the dominant programming languages used in scientific computation. Consequently, extensions to these languages are the most popular for programming massively parallel computers. We discuss two such approaches to parallel Fortran and one approach to C++. The High Performance Fortran Forum has designed HPF with the intent of supporting data parallelism on Fortran 90 applications. HPF works by asking the user to help the compiler distribute and align the data structures with the distributed memory modules in the system. Fortran-S takes a different approach in which the data distribution is managed by the operating system and the user provides annotations to indicate parallel control regions. In the case of C++, we look at pC++ which is based on a concurrent aggregate parallel model

    MILEPOST GCC: machine learning based research compiler

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    International audienceTuning hardwired compiler optimizations for rapidly evolving hardware makes porting an optimizing compiler for each new platform extremely challenging. Our radical approach is to develop a modular, extensible, self-optimizing compiler that automatically learns the best optimization heuristics based on the behavior of the platform. In this paper we describe MILEPOST GCC, a machine-learning-based compiler that automatically adjusts its optimization heuristics to improve the execution time, code size, or compilation time of specific programs on different architectures. Our preliminary experimental results show that it is possible to considerably reduce execution time of the MiBench benchmark suite on a range of platforms entirely automatically

    Trophic structure of neuston across tropical and subtropical oceanic provinces assessed with stable isotopes.

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    This research was supported by project Malaspina-2010 (CSD2008-00077) funded by program CONSOLIDERINGENIO 2010 (Ministerio de Ciencia e Innovación, Spain), by grant IN607A 2018/2 of the Axencia Galega de Innovación (GAIN, Xunta de Galicia, Spain). Thanks are also due to FCT/MCTES for the financial support to CESAM (UIDP/5 0017/2020+UIDB/50017/2020), through national funds. RA was supported by a Ph.D. fellowship funded by FCT (PD/ BD/113483/2015).The marine neuston, organisms living in the vicinity of the ocean surface, is one of the least studied zooplankton groups. Neuston occupies a restricted ecological niche and is affected by a wide range of endo- and exogenous processes, while also being a food source to zooplankton, fish migrating from the deep layers and seabirds. In this study, the neustonic communities were characterized along the Malaspina global expedition sampling tropical and subtropical oceanic provinces using stable carbon and nitrogen isotopes to explore their trophic structure and relationships with environmental variables. The differences in stable isotopes mirrored the patterns in environmental characteristics of each province. High δ13C values were associated with continental and atmospheric carbon inputs, while the presence of dinoflagellates, coccolithophorids and upwelling influence are related to low δ13C values. Similarly, provinces presenting high δ15N values were associated with denitrification and nitrate diffusive fluxes, whereas the presence of low δ15N is attributable to nitrogen supplied through N2 fixation by diazotrophs. Neuston showed a large overlap among the isotopic niches of four functional groups, with chaetognaths and detritivore generally exhibiting a smaller degree of overlap compared to carnivores and omnivores. These results support the hypothesis of a common trophic structure in the neuston community across the ocean. However, the size of the niche, small in coastal areas and those influenced by upwelling and large in oligotrophic regions, and their overlap, low in more productive provinces and high in oligotrophic provinces, may be associated with food availability. Small trophic niches are associated with a dominance of specialized over-opportunistic feeding in productive environments.This research was supported by project Malaspina-2010 (CSD2008-00077) funded by program CONSOLIDERINGENIO 2010 (Ministerio de Ciencia e Innovación, Spain), by grant IN607A 2018/2 of the Axencia Galega de Innovación (GAIN, Xunta de Galicia, Spain). Thanks are also due to FCT/MCTES for the financial support to CESAM (UIDP/5 0017/2020+UIDB/50017/2020), through national funds. RA was supported by a Ph.D. fellowship funded by FCT (PD/ BD/113483/2015).En prens

    Milepost GCC: Machine Learning Enabled Self-tuning Compiler

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    International audienceTuning compiler optimizations for rapidly evolving hardwaremakes porting and extending an optimizing compiler for each new platform extremely challenging. Iterative optimization is a popular approach to adapting programs to a new architecture automatically using feedback-directed compilation. However, the large number of evaluations required for each program has prevented iterative compilation from widespread take-up in production compilers. Machine learning has been proposed to tune optimizations across programs systematically but is currently limited to a few transformations, long training phases and critically lacks publicly released, stable tools. Our approach is to develop a modular, extensible, self-tuning optimization infrastructure to automatically learn the best optimizations across multiple programs and architectures based on the correlation between program features, run-time behavior and optimizations. In this paper we describeMilepostGCC, the first publicly-available open-source machine learning-based compiler. It consists of an Interactive Compilation Interface (ICI) and plugins to extract program features and exchange optimization data with the cTuning.org open public repository. It automatically adapts the internal optimization heuristic at function-level granularity to improve execution time, code size and compilation time of a new program on a given architecture. Part of the MILEPOST technology together with low-level ICI-inspired plugin framework is now included in the mainline GCC.We developed machine learning plugins based on probabilistic and transductive approaches to predict good combinations of optimizations. Our preliminary experimental results show that it is possible to automatically reduce the execution time of individual MiBench programs, some by more than a factor of 2, while also improving compilation time and code size. On average we are able to reduce the execution time of the MiBench benchmark suite by 11% for the ARC reconfigurable processor.We also present a realistic multi-objective optimization scenario for Berkeley DB library using Milepost GCC and improve execution time by approximately 17%, while reducing compilatio

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

    Optimisation de microcode pour une architecture horizontale et synchrone : etude et mise en oeuvre d'un compilateur

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    CNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc

    Heterogeneous Multicore Parallel Programming for Graphics Processing Units

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    Hybrid parallel multicore architectures based on graphics processing units (GPUs) can provide tremendous computing power. Current NVIDIA and AMD Graphics Product Group hardware display a peak performance of hundreds of gigaflops. However, exploiting GPUs from existing applications is a difficult task that requires non-portable rewriting of the code. In this paper, we present HMPP, a Heterogeneous Multicore Parallel Programming workbench with compilers, developed by CAPS entreprise, that allows the integration of heterogeneous hardware accelerators in a unintrusive manner while preserving the legacy code
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