High-Performance Simulations of Turbulent Clouds on a Desktop PC: Exploiting the GPU

Schalkwijk, J. C.; Griffith, Eric J.; Post, Frits H.; Jonker, Harm J. J.

doi:10.1175/bams-d-11-00059.1

Cited by 45 publications

(45 citation statements)

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“…Instead of using GPU programming models such as OpenCL 11 or CUDA 12 , which requires re-writing of the existing code (see, e.g., Schalkwijk et al, 2012, who have ported the DALES code), we have chosen the new OpenACC 13 programming model. Like OpenMP, OpenACC is based on directives that are placed, e.g., in front of loops and interpreted as comment lines by standard compilers.…”

Section: Future Perspectivesmentioning

confidence: 99%

The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives

et al. 2015

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Abstract. In this paper we present the current version of the Parallelized Large-Eddy Simulation Model (PALM) whose core has been developed at the Institute of Meteorology and Climatology at Leibniz Universität Hannover (Germany). PALM is a Fortran 95-based code with some Fortran 2003 extensions and has been applied for the simulation of a variety of atmospheric and oceanic boundary layers for more than 15 years. PALM is optimized for use on massively parallel computer architectures and was recently ported to general-purpose graphics processing units. In the present paper we give a detailed description of the current version of the model and its features, such as an embedded Lagrangian cloud model and the possibility to use Cartesian topography. Moreover, we discuss recent model developments and future perspectives for LES applications.

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Section: Future Perspectivesmentioning

confidence: 99%

The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives

et al. 2015

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“…Here, we attempt to remedy this caveat by simulating an especially large range of conditions. By utilizing the graphics processing unit (GPU), we were able to significant speed up our LES integrations, resulting in a GPU-resident atmospheric LES (GALES, see Schalkwijk et al 2012). The simulation speed of GALES allowed us to perform a continuous LES integration of the actual weather conditions at Cabauw, the Netherlands, for the full year 2012 (Schalkwijk et al 2015).…”

Section: Introductionmentioning

confidence: 99%

An Investigation of the Eddy-Covariance Flux Imbalance in a Year-Long Large-Eddy Simulation of the Weather at Cabauw

Schalkwijk

Jonker

Siebesma

2016

Boundary-Layer Meteorol

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The low-frequency contribution to the systematic and random sampling errors in single-tower eddy-covariance flux measurements is investigated using large-eddy simulation (LES). We use a continuous LES integration that covers a full year of realistic weather conditions over Cabauw, the Netherlands, and emulate eddy-covariance measurements. We focus on the daytime flux imbalance, when the turbulent flux is sufficiently resolved. Averaged over the year, daytime single-tower eddy-covariance flux measurements lead to a significant systematic underestimation of the turbulent flux. This underestimation depends on the averaging period and measurement height. For a 3600-s averaging period at 16-m height, the systematic underestimation reduces to a few percent, but for 900-s averaged tall-tower measurements at 100-m height, the fluxes are systematically underestimated by over 20 %. The year-long dataset facilitates an investigation into the environmental conditions that influence the eddy-covariance flux imbalance. The imbalance problem is found to vary widely from day to day, strongly dependent on the flow regime. In general, the imbalance problem reduces with increased mean wind speed, but days having the largest imbalance (over twice the average) are characterized by roll vortices that occur for average wind speeds, typically having a boundary-layer height (z i ) to Obukhov length (L) ratio of 10 < −z i /L < 100.

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“…In this form, they can provide an enormous computational boost, provided the programs are specifically adapted to the GPU design. A short explanation of GPU modeling is given in the sidebar.Because relatively simple parameterizations facilitate quick adaptation to a new computer architecture, we were able to create GALES, a GPU-resident Atmospheric LES (Schalkwijk et al 2012;Heus et al 2010). As a result, simulations that normally require roughly 50 processors can be performed on a single GPU with comparable speeds.…”

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confidence: 99%

Weather Forecasting Using GPU-Based Large-Eddy Simulations

Schalkwijk

Jonker

Siebesma

et al. 2015

Bulletin of the American Meteorological Society

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104

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A HISTORY OF GLOBAL NUMERICAL WEATHERPREDICTION. The spectacular development of computational resources in the past decades has had a profound impact on the field of numerical weather and climate modeling. It has facilitated significant improvements in the description of key physical processes such as radiative transfer and has led to more accurate flow solvers. In addition, it has enabled sophisticated data-assimilation and ensemble-prediction schemes, both of which have turned out to be vital for improved prediction skill. Parallel to these developments, the increased computational power has led to a gradual but steady refinement of the computational grid. This has allowed models to resolve an increasingly large portion of the atmospheric scales of motion visualized in Fig. 1. The unresolved scales need to be approximated in a statistical way through statistical parameterizations, inevitably involving uncertain The historic evolution of computational grids is illustrated in the top panel of Fig. 2, which shows how the spatial scales treated by operational global numerical weather prediction (NWP) models have evolved in time. The range of resolved scales is visualized by a horizontal bar, with the largest scale (domain size) at the right and the smallest scale (resolution) at the left. The width of the bar is therefore a key measure of computational cost. Due to ever-increasing computational resources, operational NWP models have undergone an exponential increase in horizontal resolution. This growth started in 1974 with the model of the National Meteorological Center (NMC) at 300-km resolution (denoted N74; see Shuman 1989) and continued up to the resolution of 16 km that is now used by the latest version of the European Centre for Medium-Range Weather Forecasts model (E79-E10; see e.g., Simmons et al. 1989; European Centre for Medium-Range Weather Forecasts 2014). The red bars illustrate the computational breakthroughs by Miura et al. (M06;, who simulated the global weather for one week at 3.5-km resolution, and by Miyamoto et al. (M13;, who simulated 12 h at 0.87-km resolution some years later. While such exceptional cases cannot be performed on a Operational global NWP models are presently on the verge of using resolutions finer than the depth of the troposphere, L Trop (10 km) (see Fig. 1). This implies that they are beginning to resolve the vertical convective overturning by cumulus clouds, but still need its partial parameterized representation. This obstacle, known as the "gray zone" or "Terra Incognita" (Wyngaard 2004) is like the proverbial "chasm" that cannot be crossed in small steps. Ideally the representation of convective overturning at these resolutions should be distributed smoothly (i.e., as a function of resolution), between the subgrid parameterizations on the one hand and explicit simulation on the other (Molinari and Dudek 1992;Wyngaard 2004;Arakawa et al. 2011). This can be achieved by making parameterizations "scale aware," but a general framework for such an approach is presently lackin...

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High-Performance Simulations of Turbulent Clouds on a Desktop PC: Exploiting the GPU

Abstract: No abstract available.

Cited by 45 publications

References 10 publications

The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives

The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives

An Investigation of the Eddy-Covariance Flux Imbalance in a Year-Long Large-Eddy Simulation of the Weather at Cabauw

Weather Forecasting Using GPU-Based Large-Eddy Simulations

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