OSTI.GOV Conference: Efficient Bulk Data Replication for the Earth System Grid
Title: Efficient Bulk Data Replication for the Earth System Grid
The Earth System Grid (ESG) community faces the difficult challenge of managing the distribution of massive data sets to thousands of scientists around the world. To move data replicas efficiently, the ESG has developed a data transfer management tool called the Bulk Data Mover (BDM). We describe the performance results of the current system and plans towards extending the techniques developed so far for the up- coming project, in which the ESG will employ advanced networks to move multi-TB datasets with the ulti- mate goal of helping researchers understand climate change and its potential impacts on world ecology and society.
Sim, Alex [1]; Gunter, Dan [1]; Natarajan, Vijaya [1]; Shoshani, Arie [1]; Williams, Dean [2]; Long, Jeff [2]; Hick, Jason [3]; Lee, Jason [3]; Dart, Eli [4]
+ Show Author Affiliations
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
National Energy Research Scientific Computing Center, Berkeley, CA (United States)
Energy Sciences Network, Berkeley, CA (United States)
Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (United States)
Sponsoring Org.:
USDOE; Computational Research Division
LBNL-3821E
TRN: US201017%%197
AC02-05CH11231
Resource Relation:
Conference: International Symposium on Grid Computing,
97 MATHEMATICS AND COMPUTING; CLIMATES; DISTRIBUTION; ECOLOGY; MANAGEMENT; PERFORMANCE; REPLICAS; Earth System Grid, climate data, Bulk Data Movement, data transfer, NetLogger
Sim, Alex, Gunter, Dan, Natarajan, Vijaya, Shoshani, Arie, Williams, Dean, Long, Jeff, Hick, Jason, Lee, Jason, and Dart, Eli. Efficient Bulk Data Replication for the Earth System Grid. United States: N. p., 2010. Web.
Sim, Alex, Gunter, Dan, Natarajan, Vijaya, Shoshani, Arie, Williams, Dean, Long, Jeff, Hick, Jason, Lee, Jason, & Dart, Eli. Efficient Bulk Data Replication for the Earth System Grid. United States.
Sim, Alex, Gunter, Dan, Natarajan, Vijaya, Shoshani, Arie, Williams, Dean, Long, Jeff, Hick, Jason, Lee, Jason, and Dart, Eli. Wed . "Efficient Bulk Data Replication for the Earth System Grid". United States. https://www.osti.gov/servlets/purl/986313.
@article{osti_986313,
title = {Efficient Bulk Data Replication for the Earth System Grid},
author = {Sim, Alex and Gunter, Dan and Natarajan, Vijaya and Shoshani, Arie and Williams, Dean and Long, Jeff and Hick, Jason and Lee, Jason and Dart, Eli},
abstractNote = {The Earth System Grid (ESG) community faces the difficult challenge of managing the distribution of massive data sets to thousands of scientists around the world. To move data replicas efficiently, the ESG has developed a data transfer management tool called the Bulk Data Mover (BDM). We describe the performance results of the current system and plans towards extending the techniques developed so far for the up- coming project, in which the ESG will employ advanced networks to move multi-TB datasets with the ulti- mate goal of helping researchers understand climate change and its potential impacts on world ecology and society.},
doi = {},
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Bulk Data Movement for Climate Dataset: Efficient Data Transfer Management with Dynamic Transfer Adjustment
Technical Report Sim, Alexander ; Balman, Mehmet ; Williams, Dean N. ; ...
Many scientific applications and experiments, such as high energy and nuclear physics, astrophysics, climate observation and modeling, combustion, nano-scale material sciences, and computational biology, generate extreme volumes of data with a large number of files. These data sources are distributed among national and international data repositories, and are shared by large numbers of geographically distributed scientists. A large portion of data is frequently accessed, and a large volume of data is moved from one place to another for analysis and storage. One challenging issue in such efforts is the limited network capacity for moving large datasets to explore and manage.more » The Bulk Data Mover (BDM), a data transfer management tool in the Earth System Grid (ESG) community, has been managing the massive dataset transfers efficiently with the pre-configured transfer properties in the environment where the network bandwidth is limited. Dynamic transfer adjustment was studied to enhance the BDM to handle significant end-to-end performance changes in the dynamic network environment as well as to control the data transfers for the desired transfer performance. We describe the results from the BDM transfer management for the climate datasets. We also describe the transfer estimation model and results from the dynamic transfer adjustment.« less
Scaling the Earth System Grid to 100Gbps Networks
Technical Report Balman, Mehmet ; Sim, Alex
The SC11 demonstration, titled Scaling the Earth System Grid to 100Gbps Networks, showed the ability to use underlying infrastructure for the movement of climate data over 100Gbps network. Climate change research is one of the critical data intensive sciences, and the amount of data is continuously growing. Climate simulation data is geographically distributed over the world, and it needs to be accessed from many sources for fast and efficient analysis and inter-comparison of simulations. We used a 100Gbps link connecting National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory (LBNL), Argonne National Laboratory (ANL) and Oak Ridgemore » National Laboratory (ORNL). In the demo, the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) phase 3 of the Coupled Model Intercomparison Project (CMIP-3) dataset was staged into the memory of computing nodes at ANL and ORNL from NERSC over the 100Gbps network for analysis and visualization. In general, climate simulation data consists of relatively small and large files with irregular file size distribution in each dataset. In this demo, we addressed challenges on data management in terms of high bandwidth networks, usability of existing protocols and middleware tools, and how applications can adapt and benefit from next generation networks.« less
Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4-CO 2 gas hydrate systems
Journal Article Reagan, Matthew T. ; Moridis, George J. ; Seim, Katie S. - Computers and Geosciences
A recent Department of Energy field test on the Alaska North Slope has increased interest in the ability to simulate systems of mixed CO 2-CH 4 hydrates. However, the physically realistic simulation of mixed-hydrate simulation is not yet a fully solved problem. Limited quantitative laboratory data leads to the use of various ab initio, statistical mechanical, or other mathematic representations of mixed-hydrate phase behavior. Few of these methods are suitable for inclusion in reservoir simulations, particularly for systems with large number of grid elements, 3D systems, or systems with complex geometric configurations. In this paper, we present a set ofmore » fast parametric relationships describing the thermodynamic properties and phase behavior of a mixed methane-carbon dioxide hydrate system. We use well-known, off-the-shelf hydrate physical properties packages to generate a sufficiently large dataset, select the most convenient and efficient mathematical forms, and fit the data to those forms to create a physical properties package suitable for inclusion in the TOUGH+ family of codes. Finally, the mapping of the phase and thermodynamic space reveals the complexity of the mixed-hydrate system and allows understanding of the thermodynamics at a level beyond what much of the existing laboratory data and literature currently offer.« less
DOI: 10.1016/j.cageo.2017.03.018
Gyrokinetic particle-in-cell optimization on emerging multi- and manycore platforms
Journal Article Madduri, Kamesh ; Im, Eun-Jin ; Ibrahim, Khaled Z. ; ... - Parallel Computing
The next decade of high-performance computing (HPC) systems will see a rapid evolution and divergence of multi- and manycore architectures as power and cooling constraints limit increases in microprocessor clock speeds. Understanding efficient optimization methodologies on diverse multicore designs in the context of demanding numerical methods is one of the greatest challenges faced today by the HPC community. In this paper, we examine the efficient multicore optimization of GTC, a petascale gyrokinetic toroidal fusion code for studying plasma microturbulence in tokamak devices. For GTC's key computational components (charge deposition and particle push), we explore efficient parallelization strategies across a broadmore » range of emerging multicore designs, including the recently-released Intel Nehalem-EX, the AMD Opteron Istanbul, and the highly multithreaded Sun UltraSparc T2+. We also present the first study on tuning gyrokinetic particle-in-cell (PIC) algorithms for graphics processors, using the NVIDIA C2050 (Fermi). Our work discusses several novel optimization approaches for gyrokinetic PIC, including mixed-precision computation, particle binning and decomposition strategies, grid replication, SIMDized atomic floating-point operations, and effective GPU texture memory utilization. Overall, we achieve significant performance improvements of 1.3–4.7× on these complex PIC kernels, despite the inherent challenges of data dependency and locality. Finally, our work also points to several architectural and programming features that could significantly enhance PIC performance and productivity on next-generation architectures.« less
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The impact of SciDAC on US climate change research and the IPCCAR4
Conference Wehner, Michael
SciDAC has invested heavily in climate change research. We offer a candid opinion as to the impact of the DOE laboratories' SciDAC projects on the upcoming Fourth Assessment Report of the Intergovernmental Panel on Climate Change. As a result of the direct importance of climate change to society, climate change research is highly coordinated at the international level. The Intergovernmental Panel on Climate Change (IPCC) is charged with providing regular reports on the state of climate change research to government policymakers. These reports are the product of thousands of scientists efforts. A series of reviews involving both scientists and policymakersmore » make them among the most reviewed documents produced in any scientific field. The high profile of these reports acts a driver to many researchers in the climate sciences. The Fourth Assessment Report (AR4) is scheduled to be released in 2007. SciDAC sponsored research has enabled the United States climate modeling community to make significant contributions to this report. Two large multi-Laboratory SciDAC projects are directly relevant to the activities of the IPCC. The first, entitled ''Collaborative Design and Development of the Community Climate System Model for Terascale Computers'', has made important software contributions to the recently released third version of the Community Climate System Model (CCSM3.0) developed at the National Center for Atmospheric Research. This is a multi-institutional project involving Los Alamos National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory, Argonne National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The original principal investigators were Robert Malone and John B. Drake. The current principal investigators are Phil Jones and John B. Drake. The second project, entitled ''Earth System Grid II: Turning Climate Datasets into Community Resources'' aims to facilitate the distribution of the copious amounts of data produced by coupled climate model integrations to the general scientific community. This is also a multi-institutional project involving Argonne National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The principal investigators are Ian Foster, Don Middleton and Dean Williams. Perhaps most significant among the activities of the ''Collaborative Design'', project was the development of an efficient multi-processor coupling package. CCSM3.0 is an extraordinarily complicated physics code. The fully coupled model consists of separate submodels of the atmosphere, ocean, sea ice and land. In addition, comprehensive biogeochemistry and atmospheric chemistry submodels are under intensive current development. Each of these submodels is a large and sophisticated program in its own right. Furthermore, in the coupled model, each of the submodels, including the coupler, is a separate multiprocessor executable program. The coupler package must efficiently coordinate the communication as well as interpolate or aggregate information between these programs. This regridding function is necessary because each major subsystem (air, water or surface) is allowed to have its own independent grid.« less