Deploying RMACC Summit

Anderson, J. E.; Burns, Patrick; Milroy, Daniel J.; Ruprecht, Peter; Hauser, Thomas; Siegel, Howard Jay

doi:10.1145/3093338.3093379

Cited by 61 publications

(14 citation statements)

References 4 publications

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“…With the instructions disabled, the machine passed CAM-ECT. We list results from the machines in Table 1 with FMA enabled and disabled on SUMMIT (note that the SUMMIT results can also be found in Anderson et al, 2017), and with xCORE-AVX2 (a set of optimizations that activates FMA) enabled and disabled on CHEYENNE. Finally, a third type of should pass experiments is the minimal code modifications from Milroy et al (2016) that were developed to test the variability and classification power of CESM-ECT.…”

Section: Resultsmentioning

confidence: 99%

Nine time steps: ultra-fast statistical consistency testing of the Community Earth System Model (pyCECT v3.0)

et al. 2018

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Abstract. The Community Earth System Model Ensemble Consistency Test (CESM-ECT) suite was developed as an alternative to requiring bitwise identical output for quality assurance. This objective test provides a statistical measurement of consistency between an accepted ensemble created by small initial temperature perturbations and a test set of CESM simulations. In this work, we extend the CESM-ECT suite with an inexpensive and robust test for ensemble consistency that is applied to Community Atmospheric Model (CAM) output after only nine model time steps. We demonstrate that adequate ensemble variability is achieved with instantaneous variable values at the ninth step, despite rapid perturbation growth and heterogeneous variable spread. We refer to this new test as the Ultra-Fast CAM Ensemble Consistency Test (UF-CAM-ECT) and demonstrate its effectiveness in practice, including its ability to detect small-scale events and its applicability to the Community Land Model (CLM). The new ultra-fast test facilitates CESM development, porting, and optimization efforts, particularly when used to complement information from the original CESM-ECT suite of tools.

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Section: Resultsmentioning

confidence: 99%

Nine time steps: ultra-fast statistical consistency testing of the Community Earth System Model (pyCECT v3.0)

et al. 2018

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“…Our simulations were performed at sea level using the RMACC Summit supercomputer (Anderson et al, 2017). Each simulation produced a grid of predicted magnetic field vector (B) containing the X, Y, and Z components' real and imaginary parts, so that the amplitude and phase for each component may be determined (phase was determined using tan −1 (ℑP∕ℜP), where P stands for the corresponding component of the predicted magnetic field and ℜ and ℑ, respectively, denote the real and imaginary parts).…”

Section: Forward Modeling the M 2 Magnetic Signalmentioning

confidence: 99%

A Comparison of Model‐Based Ionospheric and Ocean Tidal Magnetic Signals With Observatory Data

Schnepf

Nair

Maute

et al. 2018

Geophysical Research Letters

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Observed tidal geomagnetic field variations are due to a combination of electric currents in the ionosphere, ocean, and their induced counterparts. Using these variations to constrain subsurface electrical conductivity in oceanic regions is a promising frontier; however, properly separating the ionospheric and oceanic tidal contributions of the magnetic field is critical for this. We compare semidiurnal lunar tidal magnetic signals (i.e., the signals due to the M2 tidal mode) estimated from 64 global observatories to physics‐based forward models of the ionospheric M2 magnetic field and the oceanic M2 magnetic field. At ground level, predicted ionospheric M2 amplitudes are strongest in the horizontal components, whereas the predicted oceanic amplitudes are strongest in the vertical direction. There is good agreement between the predicted and estimated M2 phases for the Y component; however, the F and X components experience deviations that may be indicative of unmodeled ionospheric processes or unmodeled coastal effects. Overall, we find that the agreement between the physics‐based model predictions and the observations is very encouraging for electromagnetic sensing applications, especially since the predicted ionospheric vertical component is very weak.

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“…A best estimate maximum likelihood tree was generated with 100 bootstrap replicates under the GTRGAMMA model using RAxML (Stamatakis 2014). All data were processed using the University of Colorado's SUMMIT High Performance Cluster (Anderson et al 2017).…”

Section: Phylogenetic Signal In Ruelliamentioning

confidence: 99%

Evolutionary and ecological drivers of plant flavonoids across a large latitudinal gradient

Tripp

Zhuang

Schreiber

et al. 2018

Molecular Phylogenetics and Evolution

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Flavonoids are important secondary metabolites that play an integral role in protecting plants against UV radiation and other forms of environmental stress. Given widespread impacts of environmental effects associated with latitude on a multitude of biological systems and a well-documented increase in solar radiation towards the equator, plant flavonoid production is expected to increase as a response to factors associated with decreasing latitude. Using data from a Neotropical genus (Ruellia) that spans an exceptionally broad latitudinal gradient, we tested a hypothesis of a positive latitudinal gradient in flavonoid concentration and assessed other factors that influence flavonoid production including habitat type (xeric vs. wet), altitude, phylogenetic relatedness, and pleiotropic effects. Two flavones with peak absorbance in ultraviolet wavelengths, apigenin and luteolin, were detected across all species. Transcriptome data confirm high expression of the gene required for flavone biosynthesis, flavone synthase (FNS). Contrary to our prediction, data revealed a positive correlation between flavone concentration and higher latitudes. Further, we recovered strong impacts of xeric habitat, pleiotropy, and phylogenetic relatedness on flavone concentrations. This study documents a complex interplay of ecological, historical, phylogenetic relatedness, and pleiotropic factors driving plant flavonoid production.

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Deploying RMACC Summit

Cited by 61 publications

References 4 publications

Nine time steps: ultra-fast statistical consistency testing of the Community Earth System Model (pyCECT v3.0)

Nine time steps: ultra-fast statistical consistency testing of the Community Earth System Model (pyCECT v3.0)

A Comparison of Model‐Based Ionospheric and Ocean Tidal Magnetic Signals With Observatory Data

Evolutionary and ecological drivers of plant flavonoids across a large latitudinal gradient

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