Performance evaluation of a two-dimensional lattice Boltzmann solver using CUDA and PGAS UPC based parallelisation

The Unified Parallel C (UPC) language from the Partitioned Global Address Space (PGAS) family unifies the advantages of shared and local memory spaces and offers a relatively straightforward code parallelisation with the Central Processing Unit (CPU). In contrast, the Computer Unified Device Architecture (CUDA) development kit gives a tool to make use of the Graphics Processing Unit (GPU). We provide a detailed comparison between these novel techniques through the parallelisation of a two-dimensional lattice Boltzmann method based fluid flow solver. Our comparison between the CUDA and UPC parallelisation takes into account the required conceptual effort, the performance gain, and the limitations of the approaches from the application oriented developers’ point of view. We demonstrated that UPC led to competitive efficiency with the local memory implementation. However, the performance of the shared memory code fell behind our expectations, and we concluded that the investigated UPC compilers could not efficiently treat the shared memory space. The CUDA implementation proved to be more complex compared to the UPC approach mainly because of the complicated memory structure of the graphics card which also makes GPUs suitable for the parallelisation of the lattice Boltzmann method

Carbapenem-resistant Escherichia coli in Black-headed gulls, the Danube, and human clinical samples: A One Health comparison of contemporary isolates

ABSTRACT: Objectives: Our aim was to characterize and compare contemporary carbapenem-resistant Enterobacterales (CRE) isolates from gulls, the River Danube, and humans in Hungary, Budapest. Methods: Multiresistant Enterobacterales were sought for in 227 gull faecal and 24 Danube water samples from 2019 to 2020. Eosin-methylene blue agar containing 2 mg/L cefotaxime and Colilert-test containing 10 mg/L cefotaxime were used for gull and water samples, respectively. Isolates were characterized by polymerase chain reactions (PCRs); acquired carbapenemase producers were further analysed by whole-genome sequencing, together with 21 Hungarian human CR Escherichia coli (CREc) isolates. Results: Gull and water samples exhibited a CRE prevalence of 7.4% (9/122) and 6.7% (7/105), none and 5/12 water samples yielded CRE from 2019 and 2020, respectively; CRE were found only in samples taken downstream of Budapest. The dominant species was Escherichia coli and the most prevalent carbapenemase was blaNDM-1. High-risk CREc clones were found both in gulls (ST224, ST372, ST744) and the Danube (ST10, ST354, ST410); the closest associations were between ST410 from humans and the Danube, among ST1437 among gulls, and between ST1437 in gulls and the Danube (46, 0, and 22–24 allelic distances, respectively). Direct links between human and gull isolates were not demonstrated. Conclusion: The study demonstrates potential epidemiological links among humans, a river crossing a city, and urbanised birds, suggesting a local transmission network. Water bodies receiving influent wastewater, together with animals using such habitats, may serve as a local reservoir system for CRE, highlighting the importance of One Health in CRE transmission, even in a country with a low CRE prevalence in humans