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Using spatial principles to optimize distributed computing for enabling the physical science discoveries

C. Yang, H. Wu, Q. Huang, Z. Li, J. Li
2011 Proceedings of the National Academy of Sciences of the United States of America  
Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the  ...  Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences.  ...  CI to enable greater physical science discoveries.  ... 
doi:10.1073/pnas.0909315108 pmid:21444779 pmcid:PMC3078382 fatcat:dwgz4vhtzrca7j47y6y75ggb2q

Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?

Chaowei Yang, Michael Goodchild, Qunying Huang, Doug Nebert, Robert Raskin, Yan Xu, Myra Bambacus, Daniel Fay
2011 International Journal of Digital Earth  
2011) 'Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?'  ...  Huadong Guo and Changlin Wang for inviting us to write this definition and field review paper. Research  ...  His research interest is utilizing spatiotemporal principles to optimize computing for enabling science discoveries.  ... 
doi:10.1080/17538947.2011.587547 fatcat:g6jrs3avrffxddy74baqgmyhoi

The emergence of spatial cyberinfrastructure

D. J. Wright, S. Wang
2011 Proceedings of the National Academy of Sciences of the United States of America  
practice for improved synthesis and analysis of both physical and social science data.  ...  The primary focus of the articles is on spatial analyses employing distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive  ...  We are grateful to our many colleagues in the Association of American Geographers (AAG) Cyberinfrastructure Specialty Group and in the University Consortium for Geographic Information Science (UCGIS) for  ... 
doi:10.1073/pnas.1103051108 pmid:21467227 pmcid:PMC3078415 fatcat:mpisnqtpazebrdnqeiyjkbbune

Big Data and Cloud Computing [chapter]

Yun Li, Manzhu Yu, Mengchao Xu, Jingchao Yang, Dexuan Sha, Qian Liu, Chaowei Yang
2019 Manual of Digital Earth  
During the same time frame, cloud computing emerged to provide crucial computing support to address these challenges.  ...  Big data emerged as a new paradigm to provide unprecedented content and value for Digital Earth.  ...  With the virtual clusters provided by cloud computing through virtualization technology, distributed analytical platforms can be migrated to the virtual clusters from physical machine clusters, optimizing  ... 
doi:10.1007/978-981-32-9915-3_9 fatcat:n4drlq63tvfczbvfaopvkkhec4

Physical Computing for Materials Acceleration Platforms [article]

Erik Peterson, Alexander Lavin
2022 arXiv   pre-print
Here we outline a simulation-based MAP program to design computers that use physics itself to solve optimization problems.  ...  We need not be constrained by existing biases in science, mechatronics, and general-purpose computing, but rather we can pursue new vectors of engineering physics with advances in cyber-physical learning  ...  Acknowledgments & Resource Availability Lead contact Further information and requests for resources and materials should be directed to and will be fulfilled by the lead contact, Alexander Lavin (lavin  ... 
arXiv:2208.08566v1 fatcat:4scni6m4fzgbzhhawkb3j5mkim

Advancing Fusion with Machine Learning Research Needs Workshop Report

David Humphreys, A. Kupresanin, M. D. Boyer, J. Canik, C. S. Chang, E. C. Cyr, R. Granetz, J. Hittinger, E. Kolemen, E. Lawrence, V. Pascucci, A. Patra (+1 others)
2020 Journal of fusion energy  
The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies  ...  These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government  ...  Even today, following decades of research in many key areas including plasma physics and material science, much remains to be learned to enable optimization of the tokamak or other paths to fusion energy  ... 
doi:10.1007/s10894-020-00258-1 fatcat:pzk3vza7v5eytbsrg2htkr5ujq

Unsupervised Discovery of Inertial-Fusion Plasma Physics using Differentiable Kinetic Simulations and a Maximum Entropy Loss Function [article]

Archis S. Joglekar, Alexander G. R. Thomas
2022 arXiv   pre-print
We apply this to an inertial-fusion relevant configuration and find that the optimization process exploits a novel physical effect that has previously remained undiscovered.  ...  Using this framework, we perform gradient-based optimization of neural networks that provide forcing function parameters to the differentiable solver given a set of initial conditions.  ...  The authors thank the anonymous reviewers for valuable feedback towards generalizing the content for a non-plasmaphysics audience.  ... 
arXiv:2206.01637v2 fatcat:7xgpelbqb5drrdutnigsmndexm

Data-driven discovery of partial differential equations

Samuel H. Rudy, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz
2017 Science Advances  
The method provides a promising new technique for discovering governing equations and physical laws in parameterized spatiotemporal systems, where first-principles derivations are intractable.  ...  Thus, for a traveling wave, the method can distinguish between a linear wave equation and the Korteweg-de Vries equation, for instance.  ...  These first-principles derivations lead to many of the canonical models ubiquitous in physics, engineering, and the biological sciences.  ... 
doi:10.1126/sciadv.1602614 pmid:28508044 pmcid:PMC5406137 fatcat:nx6uhwsoxbcfxetd5w3cokjytm

The need for microstructure informatics in process–structure–property relations

David L. McDowell, Richard A. LeSar
2016 MRS bulletin  
Contributed oral and poster presentations and a commercial exhibition will also add to the mix. Mark your calendar today and plan to attend!  ...  Conference will provide a comprehensive overview of the latest research encompassing Metal-Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), and recent additions to the field of nanoporous  ...  The scales of structure in alloys range from several nanometers for optimal precipitate strengthening, to tens of nanometers for multilayers and nanotwins, to hundreds of nanometers for distributed coherent  ... 
doi:10.1557/mrs.2016.163 fatcat:tvbluam6tzf6dcucgfjowvff2m

Robotic Planning under Uncertainty in Spatiotemporal Environments in Expeditionary Science [article]

Victoria Preston, Genevieve Flaspohler, Anna P. M. Michel, John W. Fisher III, Nicholas Roy
2022 arXiv   pre-print
We ground our results in a real expeditionary science deployment of an autonomous underwater vehicle (AUV) in the deep ocean for hydrothermal vent discovery and characterization.  ...  We formalize expeditionary science as a sequential decision-making problem, modeled using the language of partially-observable Markov decision processes (POMDPs).  ...  Our contributions, including PLUMES [6, 7] , macro-action discovery [8] , the PHUMES model and trajectory optimizer for operational missions, and ongoing work in physically-informed deep kernel learning  ... 
arXiv:2206.01364v1 fatcat:aps5xtj6xjdhlmt2gkav5fx7ee

Physics discovery in nanoplasmonic systems via autonomous experiments in Scanning Transmission Electron Microscopy [article]

Kevin M. Roccapriore, Sergei V. Kalinin, Maxim Ziatdinov
2021 arXiv   pre-print
In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment.  ...  Compared to classical Bayesian optimization methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure-property  ...  Figure 4 . 4 DKL discovery pathway for edge plasmon search. Spatially averaged plasmon spectrum is shown in A, where the model's goal is to optimize the peak near 0.4 eV in (B).  ... 
arXiv:2108.03290v2 fatcat:qmxyazkrarcenbtsu2dfeptkoi

Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan" [article]

J. Amundson, J. Annis, C. Avestruz, D. Bowring, J. Caldeira, G. Cerati, C. Chang, S. Dodelson, D. Elvira, A. Farahi, K. Genser, L. Gray (+18 others)
2019 arXiv   pre-print
Moreover, investments in AI will be important for maintaining US leadership in the physical sciences.  ...  of Fermilab, America's premier national laboratory for High Energy Physics (HEP).  ...  Moreover, investments in AI will be important for maintaining US leadership in the physical sciences.  ... 
arXiv:1911.05796v1 fatcat:czm5vp3pgrhhhns55ocmb4el6q

Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics

Rama K. Vasudevan, Kamal Choudhary, Apurva Mehta, Ryan Smith, Gilad Kusne, Francesca Tavazza, Lukas Vlcek, Maxim Ziatdinov, Sergei V. Kalinin, Jason Hattrick-Simpers
2019 MRS Communications  
The library data enables classical correlative ML and also opens the pathway for exploration of underlying causative physical behaviors.  ...  The use of statistical/machine learning (ML) approaches to materials science is experiencing explosive growth.  ...  [53] and have led to for various computational discoveries  ... 
doi:10.1557/mrc.2019.95 pmid:32166045 pmcid:PMC7067066 fatcat:3vct5bubtnclvdjenus6pcysni

Creating Information Infrastructure for Research Collaboration

Arun Somani
2012 Merrill Series on The Research Mission of Public Universities  
new discoveries by enabling these researchers to scale up models beyond the known edges of prior work.  ...  With these thoughts in mind, how can Iowa State University best position itself to optimize the use and development of cutting-edge HPC and to lead the changes?  ...  Figure 5 : 5 Shared and Distributed Memory Machines Figure 6 : 6 Proteus Distributed Memory Machine with an Efficient and Easy to Use Hierarchical Network 5. Maximize the use of physical  ... 
doi:10.17161/merrill.2012.7869 fatcat:vv5jkokgkzbwphboezdg4ybn6i

Managing Pervasive Environments through Database Principles: A Survey [chapter]

Yann Gripay, Frédérique Laforest, Jean-Marc Petit
2009 Studies in Computational Intelligence  
However, some issues have already been tackled independently by the database community, e.g. for distributed databases or data integration.  ...  Heterogeneous devices, from small sensors to framework computers, are all linked though ubiquitous networks ranging from local peer-to-peer wireless connections to the world-wide Internet.  ...  ActiveXML is also a "framework for distributed XML data management" [6] and defines an algebra to model operations over ActiveXML documents distributed among peers, that enables query optimization.  ... 
doi:10.1007/978-3-642-02190-9_13 fatcat:xh6bgbgelbeufl2crbtrt2ulxq
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