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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

HPC resources for CMS offline computing: An integration and scalability challenge for the Submission Infrastructure

The computing resource needs of LHC experiments are expected to continue growing significantly during the Run 3 and into the HL-LHC era. The landscape of available resources will also evolve, as High Performance Computing (HPC) and Cloud resources will provide a comparable, or even dominant, fraction of the total compute capacity. The future years present a challenge for the experiments’ resource provisioning models, both in terms of scalability and increasing complexity. The CMS Submission Infrastructure (SI) provisions computing resources for CMS workflows. This infrastructure is built on a set of federated HTCondor pools, currently aggregating 400k CPU cores distributed worldwide and supporting the simultaneous execution of over 200k computing tasks. Incorporating HPC resources into CMS computing represents firstly an integration challenge, as HPC centers are much more diverse compared to Grid sites. Secondly, evolving the present SI, dimensioned to harness the current CMS computing capacity, to reach the resource scales required for the HLLHC phase, while maintaining global flexibility and efficiency, will represent an additional challenge for the SI. To preventively address future potential scalability limits, the SI team regularly runs tests to explore the maximum reach of our infrastructure. In this note, the integration of HPC resources into CMS offline computing is summarized, the potential concerns for the SI derived from the increased scale of operations are described, and the most recent results of scalability test on the CMS SI are reported.

Pérez-Calero Yzquierdo, Antonio↗
DOE OSTI2018

Future Online Analysis Platform Workshop Report

Recent technology trends, such as the increasing focus on data management technologies and the emergence of sustainable on-demand computing and commercial cloud facilities provide initial steps and potential building blocks for creating such a compute facility. How do we fill the gap between what we have now and the capabilities we need to make the vision of an online data facility a reality? What research challenges need to be addressed – and can be addressed – in the coming 5-10 years? How should we adjust our vision if they are not solved? Is such a facility compatible with the existing and evolving exascale resources and/or how should they evolve to be compatible? How do “beyond Moore’s law” technologies enable advanced data analysis? Those are the challeges that the Future Platform workshop was organized to address. This report is organized as follows. Section 2 summarizes data challenges and patterns related to the exemplar use cases presented during the first half day of the workshop. Section 3 summarizes the requirements presented by those use cases as well as a synthesis of those requirements into a Future Platform definition achieved on the 3rd half day of the workshop (morning of the 2nd day). Section 4 includes area breakout reports from the areas on the 2nd half day of the workshop (afternoon of the 1st day). Finally Section 5 has a report on recommendation for building methodology and metrics. The report concludes in Section 6.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)

The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.

cloud computing↗
NASA NTRS2006

A Fast Infrared Radiative Transfer Model for Overlapping Clouds

A fast infrared radiative transfer model (FIRTM2) appropriate for application to both single-layered and overlapping cloud situations is developed for simulating the outgoing infrared spectral radiance at the top of the atmosphere (TOA). In FIRTM2 a pre-computed library of cloud reflectance and transmittance values is employed to account for one or two cloud layers, whereas the background atmospheric optical thickness due to gaseous absorption can be computed from a clear-sky radiative transfer model. FIRTM2 is applicable to three atmospheric conditions: 1) clear-sky, 2) single-layered ice or water cloud, and 3) two simultaneous cloud layers in a column (e.g., ice cloud overlying water cloud). Moreover, FIRTM2 outputs the derivatives (i.e., Jacobians) of the TOA brightness temperature with respect to cloud optical thickness and effective particle size. Sensitivity analyses have been carried out to assess the performance of FIRTM2 for two spectral regions, namely the longwave (LW) band (587.3 - 1179.5/cm) and the short-to-medium wave (SMW) band (1180.1 - 2228.9/cm). The assessment is carried out in terms of brightness temperature differences (BTD) between FIRTM2 and the well-known discrete ordinates radiative transfer model (DISORT), henceforth referred to as BTD (F-D). The BTD (F-D) values for single-layered clouds are generally less than 0.8 K. For the case of two cloud layers (specifically ice cloud over water cloud), the BTD(F-D) values are also generally less than 0.8 K except for the SMW band for the case of a very high altitude (>15 km) cloud comprised of small ice particles. Note that for clear-sky atmospheres, FIRTM2 reduces to the clear-sky radiative transfer model that is incorporated into FIRTM2, and the errors in this case are essentially those of the clear-sky radiative transfer model.

Niu, Jianguo↗
NASA NTRS1986

Translucent molecular clouds: Theory and observations

Few suitable stars behind molecular clouds have been identified. A limited survey was performed of interstellar lines toward highly reddened stars in the southern sky, using the ESO 1.4 m CAT telescope with a Reticon detector, and the Cerro Tololo 4 m telescope equipped with a GEC charge coupled device (CCD) detector. Because of the reduced extinction at longer wavelengths, molecules were searched for with transitions in the red part of the spectrum such as C2 and CN. For some lines-of-sight for which C2 was detected, the 4300 A line of CH was also observed. Absorption lines of interstellar C2 around 8750 A were detected in the spectra of about 1/4 of the 36 observed stars. The inferred C2 column densities range between 10 to the 13th power and 10 to the 14th power sq. cm., and are up to an order of magnitude larger than those found for diffuse clouds. The observed column densities of CH correlate very well with those of C2 over this range. In contrast, the measured column densities of CN vary by orders of magnitude between the various regions, and they do not correlate with those of C2 and CH. The observed rotational population distribution of C2 also provides information about the physical conditions in the clouds. Models of translucent molecular clouds have been constructed along the lines described by van Dishoeck and Black (1986) for diffuse clouds. The models compute accurately the fractions of atomic and molecular hydrogen as functions of depth into the clouds, as well as the excitation of H2 by ultraviolet pumping. They also incorporate a detailed treatment of the photodissociation processes of the molecules (cf. van Dishoeck 1986), which play an important role in the chemistry up to depths of about 3 mag.

Vandishoeck, E. F.↗
NASA NTRS2016

Big Data in the Earth Observing System Data and Information System

Approaches that are being pursued for the Earth Observing System Data and Information System (EOSDIS) data system to address the challenges of Big Data were presented to the NASA Big Data Task Force. Cloud prototypes are underway to tackle the volume challenge of Big Data. However, advances in computer hardware or cloud won't help (much) with variety. Rather, interoperability standards, conventions, and community engagement are the key to addressing variety.

data systems↗
DOE OSTI2015

Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR

Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify and analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.

Clustering↗
DOE OSTI2022

Physics-guided machine learning for improved accuracy of the National Solar Radiation Database

The National Solar Radiation Database (NSRDB) provides high-resolution spatiotemporal solar irradiance data for the entire globe. The NSRDB uses a two-step Physical Solar Model (PSM) to compute the effects of clouds and other atmospheric variables on the solar radiation reaching the surface of the Earth. Physical and optical cloud properties are fundamental inputs to the PSM and are derived from the National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellites. This paper describes recent improvements to the NSRDB driven by physics-guided machine learning methods for cloud property retrieval. The impacts of these new methods on the NSRDB irradiance data are validated using an extensive set of ground measurement sites, showing significant improvement for all sites. We report on average, the mean absolute percentage error for global horizontal irradiance and direct normal irradiance show reductions of 2.16 and 3.95 percentage points respectively for all daylight conditions, 5.92 and 17.39 percentage points respectively for cloudy conditions, and 9.00 and 22.59 percentage points respectively for gap-filled cloudy conditions. These new methods will help improve the quality and accuracy of the irradiance and cloud data in the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2021

Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF’s summit supercomputer

Clouds represent a key uncertainty in future climate projection. While explicit cloud resolution remains beyond our computational grasp for global climate, we can incorporate important cloud effects through a computational middle ground called the Multi-scale Modeling Framework (MMF), also known as Super Parameterization. This algorithmic approach embeds high-resolution Cloud Resolving Models (CRMs) to represent moist convective processes within each grid column in a Global Climate Model (GCM). The MMF code requires no parallel data transfers and provides a self-contained target for acceleration. This study investigates the performance of the Energy Exascale Earth System Model-MMF (E3SM-MMF) code on the OLCF Summit supercomputer at an unprecedented scale of simulation. Hundreds of kernels in the roughly 10K lines of code in the E3SM-MMF CRM were ported to GPUs with OpenACC directives. A high-resolution benchmark using 4600 nodes on Summit demonstrates the computational capability of the GPU-enabled E3SM-MMF code in a full physics climate simulation.

58 GEOSCIENCES↗
NASA NTRS2004

A New Approach to Using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Recently Grabowski and Khairoutdinov and Randall have proposed and demonstrated, the feasibility of using 2D CRMs (these did not include detailed land processes and used periodic lateral boundary conditions) as 'super-parameterizations or a multi-scale modeling framework MMF' for cloud processes within atmospheric generation circulation models (GCMs). In the MMF, a fine-resolution 2D CRM takes the place of the single-column parameterization that is used in conventional GCMs. An overview of this approach is given by Randall et al.. Since a CRM can explicitly simulate cloud processes at the natural space and time scales of clouddynamical processes, it's possible to compute statistics of cloud fields, including radiances and radar backscatters, directly simulated/produced by the CRM. A seed fund is available at NASA Goddard to build a MMF based on a 2D GCE model and the Goddard fvGCM. A prototype MMF will be developed at end of 2004. The major objectives are to test and evaluate its performance using the GCE model as the super parameterization and compare its results with other super parameterizations, conventional GCMs and observations. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (WE) model. The GCE model is a CRM and it has been improved and applied to study the precipitation processes in the past two decades. Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated. In addition, the similarities and differences between bulk- and spectral-bin microphysics will be presented,

Tao, Wei-Kuo↗
NASA NTRS1985

X-ray secondary heating and ionization in quasar emission-line clouds

Accurate Monte Carlo computations of the X-ray secondary electron heating, ionization, and excitation of H and He gas in interstellar space and in quasar emission-line clouds, are presented. The fraction of energy deposited in each form is sensitive to the background ionization fraction, x = n(H+)/n(Htot), and can affect the temperature, ionization state, and line emissivities at large depths in X-ray photoionized clouds. Analytic fits are provided for these energy fractions over the range 0.0001-1 for primary electron energies up to many keV. In both broad-line and narrow-line clouds, emission lines sensitive to the energy budget and electron density may be strongly affected.

Shull, J. M.↗
NASA NTRS2012

RACORO Extended-Term Aircraft Observations of Boundary-Layer Clouds

Small boundary-layer clouds are ubiquitous over many parts of the globe and strongly influence the Earths radiative energy balance. However, our understanding of these clouds is insufficient to solve pressing scientific problems. For example, cloud feedback represents the largest uncertainty amongst all climate feedbacks in general circulation models (GCM). Several issues complicate understanding boundary-layer clouds and simulating them in GCMs. The high spatial variability of boundary-layer clouds poses an enormous computational challenge, since their horizontal dimensions and internal variability occur at spatial scales much finer than the computational grids used in GCMs. Aerosol-cloud interactions further complicate boundary-layer cloud measurement and simulation. Additionally, aerosols influence processes such as precipitation and cloud lifetime. An added complication is that at small scales (order meters to 10s of meters) distinguishing cloud from aerosol is increasingly difficult, due to the effects of aerosol humidification, cloud fragments and photon scattering between clouds.

boundary layer↗
NASA NTRS1992

Longwave radiation budget parameters computed from ISCCP and HIRS2/MSU products

The International Satellite Cloud Climatology Project (ISCCP) retrieved cloud fields and the high-resolution radiation sounder 2 (HIRS2) retrieved cloud fields yield similar outgoing longwave radiation (OLR) due to the cancelation effect of cloud-top altitudes and cloud amount on OLR. For the large regional discrepancies of the order of 30 W/sq m found over northern Africa are largely due to surface temperature differences, and extensive discrepancies over the ocean are due to humidity differences. Harmonic analysis is applied to OLR, clear-sky OLR, and cloud-radiative forcing at the top of the atmosphere using the ISCCP products. The diurnal variations of these parameters from 60 deg S to 60 deg N are larger over land than over the ocean. The clear-sky OLR peaks around 1500 LST, usually over land areas, and is associated with the surface/air temperature maximum. The OLR over cloudy regions shows a similar diurnal phase as the cloud top pressure. The cloud radiative forcing at the top of the atmosphere has maximum value near 2100 LST mountain areas and near 0000 and 0300 LST over equatorial regions. The ISCCP-computed longwave cloud radiative forcing has smaller diurnal variations over the ocean than the HIRS2-computed longwave cloud radiative forcing. The global mean bias of OLR is around 0.74 W/sq m, and locally, the bias can be as large as 5 to 10 W/sq m. This appears to indicate that the twice-a-day measurements of the HIRS2/MSU (around 0315 and 1515 LST, which are the equatorial cross times at nadir track) can be used to derive monthly mean OLR without significant bias.

Wu, Man L. C.↗
DOE OSTI2022

Secure Collaborative Environment for Seamless Sharing of Scientific Knowledge

In a secure collaborative environment, tera-bytes of data generated from powerful scientific instruments are used to train secure machine learning (ML) models on exascale computing systems, which are then securely shared with internal or external collaborators as cloud-based services. Devising such a secure platform is necessary for seamless scientific knowledge sharing without compromising individual, or institute-level, intellectual property and privacy details. By enabling new computing opportunities with sensitive data, we envision a secure collaborative environment that will play a significant role in accelerating scientific discovery. Several recent technological advancements have made it possible to realize these capabilities. In this paper, we present our efforts at ORNL toward developing a secure computation platform. We present a use case where scientific data generated from complex instruments, like those at the Spallation Neutron Source (SNS), are used to train a differential privacy enabled deep learning (DL) network on Summit, which is then hosted as a secure multi-party computation (MPC) service on ORNL’s Compute and Data Environment for Science (CADES) cloud computing platform for third-party inference. In this feasibility study, we discuss the challenges involved, elaborate on leveraged technologies, analyze relevant performance results and present the future vision of our work to establish secure collaboration capabilities within and outside of ORNL.

Yoginath, Srikanth↗
NASA NTRS1984

Stratocumulus cloud field reflected fluxes - The effect of cloud shape

The reflected fluxes of stratocumulus cloud fields are calculated as a function of sky cover aspect ratio and cloud shape. In order to obtain a better fit with general circulation models (GCMs), cloud liquid water volume values were kept invariant relative to cloud shape. On the basis of the required accuracy of the Earth Radiation Budget Experiment (ERBE), an order of magnitude value of 10 W per sq m was used to estimate the difference between plane-parallel and broken cloudiness reflected fluxes. An empirical relationship for effective cloud cover at a solar zenith angle of 60 deg is derived. The relationship allows for the accurate computation of broken cloud field reflected fluxes using plane-parallel calculations. It is predicted that more accurate estimates of broken cloud field radiative properties may be possible in the future.

Welch, R. M.↗
NASA NTRSDate not supplied

Earth Radiation Budget Climate Record Composed of Multiple Satellite Observations

Effects of cloud diurnal cycle on top-of-atmosphere (TOA) and surface regional monthly mean irradiances, climatological mean, and anomalies are analyzed using CERES derived TOA irradiances and surface irradiances computed with MODIS derived cloud properties. Cloud properties derived from Terra and Aqua MODIS are sufficient to capture cloud diurnal cycle to compute regional monthly mean surface irradiances. While missing cloud diurnal cycle leads to a biased TOA and surface regional irradiances for regions with a strong cloud diurnal cycle, monthly regional TOA and surface anomalies derived from one sun-synchronous orbit agrees well with those derived from two sun-synchronous orbits. Based on these results, the algorithm to produce Edition 4.2 CERES EBAF product is developed. Regional TOA and surface climatological means derived from one sun-synchronous orbit are adjusted to match corresponding climatological means derived from Terra+Aqua observations. This climatological adjustment approach is used to merge the Terra only period to the Terra+Aqua period and to extend the Terra and Aqua record by merging NOAA20 observations. Two additional differences of Edition 4.2 EBAF algorithm to compute surface irradiances compared to the earlier version are: 1) no geostationary satellite derived cloud properties are used and 2) temperature and humidity from MERRA-2 instead of GEOIS-5.4.1 are used. Once surface monthly regional mean irradiances are compared with surface observations, the agreement is equivalent to the agreement with the earlier version. However, because surface irradiances are not affected by geostationary satellite artifacts, regional surface irradiance anomaly time series is significantly improved, especially for longwave irradiances.

Seiji Kato↗
DOE OSTI2022

Idealized Simulations of the Tropical Climate and Variability in the Single Column Atmosphere Model (SCAM): Radiative-Convective Equilibrium

To explore the interactions among column processes in the Community Atmosphere Model (CAM), the single-column version of CAM (SCAM) is integrated for 1000 days in radiative-convective equilibrium (RCE) with tropical values of boundary conditions, spanning a parameter or configuration space of model physics versions (v5 vs. v6), vertical resolution (standard and 60 levels), sea surface temperature (SST), and some interpretation-driven experiments. The simulated time-mean climate is reasonable, near observations and RCE of a cyclic cloud-resolving model. Updraft detrainment in the deep convection scheme produces distinctive grid-scale structures in humidity and cloud, which also interact with radiative transfer processes. These grid artifacts average out in multi-column RCE results reported elsewhere, illustrating the nuts-and-bolts interpretability that SCAM adds to the hierarchy of model configurations. Multi-day oscillations of precipitation arise from descent of warm convection-capping layers starting near the tropopause, eventually reset by a burst of convective deepening. Experiments reveal how these oscillations depend critically on an internal parameter that controls the number of neutral buoyancy levels allowed for determining cloud top and computing dilute convective available potential energy in the deep convection scheme, and merely modified a little by disabling cloud-base radiation (heating of cloud base). This strong dependence of transient behavior in 1D on this parameter will be tested in the second part of this work, in which SCAM is coupled to a parameterized dynamics of two-dimensional, linearized gravity wave, and in the 3D simulations in future study.

Meteorology & Atmospheric Sciences↗
NASA NTRS2003

Electrical Charging of the Clouds of Titan

We have used recent data on graphitic cloud particles in the atmosphere or Titan to compute the electrical charging of the particles (radii ranging from 0.01 microns to 0.26 microns). The charging on the nightside was rather similar to that obtained earlier (Borucki et al, Icarus, 72, 604-622, 1987) except that charge distributions on the particles are now computed and recently obtained cloud particle sizes and density distributions were employed. The negative charge on particles of 0.26 microns peaked at 9 at 150 km altitude. The computations were repeated for the dayside with the addition of photoelectron emission by the particles as a result of the absorption of solar UV radiation. Particles (except the very smallest) now became positively charged with particles of radius 0.26 microns being charged up to +47. Next, very small particles (radii approximately 3 x 10^-4 microns) of polycyclic aromatic hydrocarbons (PAHs) were introduced and treated as sources of negative ions since they could be either neutral or carry one negative charge. Moreover, they are mobile so that they had to be treated like molecular size negative ions although much more massive. They had the effect of substantially reducing the electron densities in the altitude range 190 to 310 km to values less than the negative PAH densities and increasing the peak electron charge on the larger particles. Particles of radius 0.26 microns bore peak charges of plus or minus 47 at altitudes of approximately 250 km. The simulated effect of PAHs on the nightside proved to be much less pronounced; at the peak negative PAH density, it was less than the electron density. The physics governing these results will be discussed.

Borucki, William J.↗