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13 results for “exascale”
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - Simuation results and observed data
<p>This data set contains the simulation results and observed data at NDBC buoy locations.</p> <ul> <li>wave_data.pickle <ul> <li>File containing python data objects which store: station ID data, observed data, model data, and model output dates. Requires python 3.8.</li> </ul> </li> <li>data_access.py <ul> <li>Example python script which reads in a prints the data from wave_data.pickle. It also demonstrates how to access data from the objects stored in the pickle file.</li> </ul> </li> </ul>
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - 2 degree WaveWatchIII configuration files
<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a 2 degree structured grid.</p> <ul> <li>glo_2d.bot <ul> <li>Bottom depth file for 2 degree structured grid</li> </ul> </li> <li>glo_2d.mask <ul> <li>Mask file for 2 degree structured grid</li> </ul> </li> <li>obstructions_local.glo_2d.in <ul> <li>local obstructions file for use with UOST source term switch</li> </ul> </li> <li>obstructions_shadow.glo_2d.in <ul> <li>shadow obstructions file for use with UOST source term switch</li> </ul> </li> <li>ww3_grid.inp <ul> <li>Input file for the ww3_grid pre-processing program. This file specifies many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - unstructured (2 degree to 1/2 degree) WaveWatchIII configuration files
<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a global ustructured grid.</p> <ul> <li>mesh.msh <ul> <li>Unstructured mesh file in gmsh format. The unstructured mesh has 2 degree resolution globally with 1/2 degree resolution around the U.S. coastlines. The transition in resolution occurs at 4000m depth with a 10% resolution grading.</li> </ul> </li> <li>obstructions_local.glo_unst.in <ul> <li>local obstructions file for use with UOST source term switch</li> </ul> </li> <li>obstructions_shadow.glo_unst.in <ul> <li>shadow obstructions file for use with UOST source term switch</li> </ul> </li> <li>ww3_grid.inp <ul> <li>Input file for the ww3_grid pre-processing program. This file specifies many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>
Exascale Potholes for HPC: Execution Performance and Variability Analysis of the Flagship Application Code HemeLB
<p>Performance measurement and analysis of parallel applications is often challenging, despite many excellent commercial and open-source tools being available. Currently envisaged exascale computer systems exacerbate matters by requiring extremely high scalability to effectively exploit millions of processor cores. Unfortunately, significant application execution performance variability arising from increasingly complex interactions between hardware and system software makes this situation much more difficult for application developers and performance analysts alike.<br> </p> <p>This work considers the performance assessment of the HemeLB exascale flagship application code from the EU HPC Centre of Excellence (CoE) for Computational Biomedicine (CompBioMed) running on the SuperMUC-NG Tier-0 leadership system, using the methodology of the Performance Optimisation and Productivity (POP) CoE. Although 80% scaling efficiency is maintained to over 100,000 MPI processes, disappointing initial performance with more processes and corresponding poor strong scaling was identified to originate from the same few compute nodes in multiple runs, which later system diagnostic checks found had faulty DIMMs and lacklustre performance. Excluding these compute nodes from subsequent runs improved performance of executions with over 300,000 MPI processes by a factor of five, resulting in 190x speed-up compared to 864 MPI processes. While communication efficiency remains very good up to the largest scale, parallel efficiency is primarily limited by load balance found to be largely due to core-to-core and run-to-run variability from excessive stalls for memory accesses, that affect many HPC systems with Intel Xeon Scalable processors. The POP methodology for this performance diagnosis is demonstrated via a detailed exposition with widely deployed `standard' measurement and analysis tools.</p>
The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale
<p>Data and figures presented in the paper "The ESCAPE project: Energy-efficient scalable algorithms for weather prediction at exascale". The discussion paper is available at: https://doi.org/10.5194/gmd-2018-304</p>
An Assessment of Nonhydrostatic and Hydrostatic Dynamical Cores at Seasonal Time Scales in the Energy Exascale Earth System Model (E3SMv1)
<p>This is the companion data for the manuscript of the same title, submitted to Journal of Advances in Modeling Earth Systems on 09/03/2021. </p> <p><strong>summer: </strong>this folder contains part of the model outputs I ran on NERSC Cori in 2020-2021 corresponding to the summer simulations in the manuscript.</p> <p><strong>winter: </strong>this folder contains part of the outputs I ran on NERSC Cori in 2020-2021 corresponding to the winter simulations in the manuscript.</p> <p><strong>ne256: </strong>this folder contains part of the outputs I ran on NERSC Cori in 2021 corresponding to the ne256 simulations in the manuscript.</p> <p><strong>bubble</strong>: this folder includes the namelists used in the rising bubble experiments.</p> <p><strong>script: </strong>this folder includes an example of a script to generate the realistic SCREAM simulation </p> <p> </p> <p>Unfortunately, model outputs are too large (~ 30 TB). Therefore, I only provide mean data, used directly to generate figures, in this repository. All model output are archived on tape at NERSC. </p> <p>For more details, refer to the manuscript, or contact me (wrliu@ucdavis.edu). </p>
Data for WarpX Milestone ECP-ADSE06.FY23.2: Progress towards the full exascale challenge problem
<p><strong>Artifact Description</strong></p> <p>See https://zenodo.org/record/7790160 (and update).</p> <p>Milestone data for year 7, milestone 2 (WBS 2.2.2.6, Milestone ECP-ADSE06.FY23.2).</p>
Diurnal rainfall response to the physiological and radiative effects of CO2 in tropical forests in the Energy Exascale Earth System Model v1
<p>Necessary outputs and scripts for recreating the figures for the journal article with the same title.</p>
Supplementary Materials: Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale
<p>Supplementary materials (aka data artifact or data archive) for our NAPAC22 publication: "Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale" (Paper ID: TUYE2).</p> <p>Work supported by the Exascale Computing Project (17-SC-20-SC), a joint project of the U.S. Department of Energy's Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation's exascale computing imperative. This work was supported by the Laboratory Directed Research and Development Program of Lawrence Berkeley National Laboratory under U.S. Department of Energy Contract No. DE-AC02-05CH11231.<br> This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231.</p>
Co-assembly of 98TBs of metagenomes from human gut using exascale assembler MetaHipMer
Open the record for dataset details and reuse information.
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - 1/2 degree WaveWatchIII configuration files
<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a 1/2 degree structured grid.</p> <ul> <li>glo_30m.bot <ul> <li>Bottom depth file for a 1/2 degree structured grid</li> </ul> </li> <li>glo_30m.mask <ul> <li>Mask file for a 1/2 degree structured grid</li> </ul> </li> <li>obstructions_local.glo_30m.in <ul> <li>local obstructions file for use with UOST source term switch</li> </ul> </li> <li>obstructions_shadow.glo_30m.in <ul> <li>shadow obstructions file for use with UOST source term switch</li> </ul> </li> <li>ww3_grid.inp <ul> <li>Input file for the ww3_grid pre-processing program. This file specifies many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>
Data for WarpX milestone ECP-ADSE06.FY21.2: Assessment of dynamic load-balancing strategies on available exascale systems.
<p>This dataset includes the inputs, outputs, job submission scripts, and data analysis scripts used to prepare the WarpX milestone report for "Assessment of dynamic load-balancing strategies on available exascale systems." The code versions of WarpX, AMReX, and PICSAR used are stored in the outputs file for each run. </p>
Ocean Dynamics in the DOE Energy, Exascale, Earth System Model (E3SM)
<p>Climate research at the U.S. Department of Energy (DOE) includes the development of ocean, sea-ice, atmosphere, land-vegetation and land-ice models. The ability to run high-resolution global simulations efficiently on the world’s largest computers is a priority for the DOE. This movie shows simulations from the variable-resolution ocean model, the Model for Prediction Across Scales (MPAS-Ocean), which is developed at Los Alamos National Laboratory. MPAS-Ocean is a component of the DOE’s newly released Energy, Exascale, Earth System Model (E3SM). Applications of E3SM include the simulation of 20th-century and future climate scenarios, as well as special configurations where model resolution is enhanced in regions of particular interest, like coastal areas, the Arctic, or below Antarctic ice shelves.</p> <p>Website: <a href="https://e3sm.org">https://e3sm.org</a>. </p>
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