Automatic Parallelization of a Gap Model using Java and OpenCL

International audienceNowadays, scientists are often disappointed by the outcome when parallelizing their simulations, in spite of all the tools at their disposal. They often invest much time and money, and do not obtain the expected speed-up. This can come from many factors going from a wrong parallel architecture choice to a model that simply does not present the criteria to be a good candidate for parallelization. However, when parallelization is successful, the reduced execution time can open new research perspectives, and allow to explore larger sets of parameters of a given simulation model. Thus, it is worth investing some time and workforce to figure out whether an algorithm is a good candidate to parallelization. Automatic parallelization tools can be of great help when trying to identify these properties. In this paper, we apply an automatic parallelization approach combining Java and OpenCL on an existing Gap Model. The two technologies are linked with a library from AMD called Aparapi. The latter allowed us to study the behavior of our automatically parallelized model on 10 different platforms, without modifying the source code

Antibiotic resistant Escherichia coli in waters of the Seine river basin (France)

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Presence and origin of antibiotic resistant Eschercichia coli in waters of the Seine river basin (France)

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Rejets hospitaliers d’antibiotiques et de bactéries fécales antibiorésistantes dans les rivières du bassin de la Seine

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Occurrence et origines des bactéries fécales antibiorésistantes (E. coli et entérocoques) dans le bassin de la Seine

Etude réalisée dans le cadre du programme de interdisciplinaire de recherche PIREN-Seine (CNRS)info:eu-repo/semantics/publishe

Antimicrobial resistance of fecal bacteria in waters of the Seine river watershed (France).

We studied the prevalences of antimicrobial resistance (AR) and multiple antimicrobial resistance (MAR)among the fecal bacteria found in the rivers of a large watershed under strong anthropogenic pressures, the Seine river watershed (France). Two groups of fecal indicator bacteria, Escherichia coli and intestinal enterococci, were tested for their susceptibility to 16 and 10 antimicrobials respectively, using the disk diffusion method. We found that 42% of the 214 E. coli river isolates were AR (resistant to at least one antimicrobial) and 35% were MAR (resistant to at least two antimicrobials). Among the 148 intestinal enterococci isolates from rivers, 83% were AR and 49% were MAR. We also investigated the sources of AR fecal bacteria found in the rivers of the watershed. A total of 715 E. coli isolates and 476 intestinal enterococci isolates were collected in point sources (municipal and hospital wastewaters) and non-point sources (surface runoff and soil leaching waters from agricultural or forest areas). For E. coli, the prevalence of AR differed widely from source to source and ranked in this order: hospital wastewaters (71%)>municipal wastewaters (44%)>agricultural non-point sources (16%)>forest non-point sources (2%). The prevalence of MAR ranked similarly, and the same trend was observed for intestinal enterococci. The AR level of fecal bacteria in the sources was related to their expected exposure level to antimicrobials before their release into the environment. A MAR index was calculated for every source and a good discrimination between them was thus obtained. At the global scale of the Seine river watershed, domestic wastewaters seemed more likely to be the predominant source of the AR fecal bacteria found in the rivers. This was corroborated by the similarity of the MAR indices from river and municipal wastewater isolates for both fecal indicators.info:eu-repo/semantics/publishe

Antibiorésistance des flores bactériennes autochtone et fécale dans les rivières du bassin de la Seine

Etude réalisée dans le cadre du programme de interdisciplinaire de recherche PIREN-Seine (CNRS)info:eu-repo/semantics/publishe

Dynamique des bactéries indicatrices de contamination fécale dans les rivières du bassin de l’Escaut

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Modelling microbiological contamination in the Scheldt river basin

A contribution to the PAI project: Tracing and Integrated Modeling of Natural and Anthropogenic Effects on Hydrosystems :The Scheldt River Basin and Adjacent Coastal North Sea (TIMOTHY)info:eu-repo/semantics/publishe

Impact d’un rejet urbain de temps de pluie en Seine sur la qualité microbiologique des eaux

Etude réalisée dans le cadre du programme de interdisciplinaire de recherche PIREN-Seineinfo:eu-repo/semantics/publishe