LEADER 01179nam 2200361 n 450 001 996389833903316 005 20221108025347.0 035 $a(CKB)1000000000646209 035 $a(EEBO)2240953456 035 $a(UnM)99870167 035 $a(EXLCZ)991000000000646209 100 $a19940819d1660 uy | 101 0 $aeng 135 $aurbn||||a|bb| 200 02$aA free Parliament proposed by the City to the nation$b[electronic resource] 210 $a[London $cs.n.$d1660] 215 $a1 sheet ([1] p.) 300 $aAnonymous. By Sir Roger L'Estrange. 300 $aImprint from Wing. 300 $aDated: Decemb. 6. 1659. 300 $aReproduction of the original in the British Library. 330 $aeebo-0018 607 $aGreat Britain$xPolitics and government$y1649-1660$vEarly works to 1800 607 $aLondon (England)$xHistory$y17th century$vEarly works to 1800 702 $aL'Estrange$b Roger$cSir,$f1616-1704, 801 0$bCu-RivES 801 1$bCu-RivES 801 2$bCStRLIN 801 2$bWaOLN 906 $aBOOK 912 $a996389833903316 996 $aA free Parliament proposed by the City to the nation$92413685 997 $aUNISA LEADER 06553nam 22007575 450 001 996508666903316 005 20240216185831.0 010 $a3-031-23606-8 024 7 $a10.1007/978-3-031-23606-8 035 $a(MiAaPQ)EBC7179470 035 $a(Au-PeEL)EBL7179470 035 $a(CKB)26027649100041 035 $a(DE-He213)978-3-031-23606-8 035 $a(PPN)267807945 035 $a(EXLCZ)9926027649100041 100 $a20230117d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAccelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation$b[electronic resource] $e22nd Smoky Mountains Computational Sciences and Engineering Conference, SMC 2022, Virtual Event, August 23?25, 2022, Revised Selected Papers /$fedited by Kothe Doug, Geist Al, Swaroop Pophale, Hong Liu, Suzanne Parete-Koon 205 $a1st ed. 2022. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2022. 215 $a1 online resource (406 pages) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v1690 311 08$aPrint version: Doug, Kothe Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation Cham : Springer,c2023 9783031236051 320 $aIncludes bibliographical references and index. 327 $aFoundational Methods Enabling Science in an Integrated Ecosystem -- Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models -- Self-learning Data Foundation for Scientific AI -- Preconditioners for batched iterative linear solvers on GPUs -- Mobility Aware Computation Offloading Model for Edge Computing -- Science and Engineering Applications Requiring and Motivating an Integrated Ecosystem -- Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials -- A Vision for Coupling Operation of US Fusion Facilities with HPC Systems and the Implications for Workflows and Data Management -- At-the-edge Data Processing for Low Latency High Throughput Machine Learning Algorithms -- Implementation of a framework for deploying AI inference engines in FPGAs -- Systems and Software Advances Enabling an Integrated Science and Engineering Ecosystem -- Calvera: A Platform for the Interpretation and Analysis of Neutron Scattering Data -- Virtual Infrastructure Twins: Software Testing Platforms for Computing and Instrument Ecosystems -- The INTERSECT Open Federated Architecture for the Laboratory of the Future -- Real-Time Edge Processing During Data Acquisition -- Towards a Software Development Framework for Interconnected Science Ecosystems -- Deploying Advanced Technologies for an Integrated Science and Engineering Ecosystem -- Adrastea: An Efficient FPGA Design Environment for Heterogenous Scientific Computing and Machine Learning -- Toward an Autonomous Workflow for Bragg Peak Detection at SNS -- Industrial experience deploying heterogeneous platforms for use in multi-modal power systems design workflows -- Self-Describing Digital Assets and their applications in an Integrated Science and Engineering Ecosystem -- Simulation Workflows in Minutes, at Scale for Next-Generation HPC -- Scientific Data Challenges -- Machine Learning approaches to High Throughput Phenotyping -- SMC 2022 Data Challenge: Summit Spelunkers Solution for Challenge 2 -- Usage Pattern Analysis for The Summit Login Nodes -- Finding Hidden Patterns in High Resolution Wind Flow Model Simulations -- Investigating Relationships in Environmental and Community Health: Correlations Of Environment, Urban Morphology, And Socio-Economic Factors In The Los Angeles Metropolitan Statistical Area -- Patterns and Predictions: Generative Adversarial Networks for Neighborhood Generation. 330 $aThis book constitutes the refereed proceedings of the 22nd Smoky Mountains Computational Sciences and Engineering Conference on Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, SMC 2022, held virtually, during August 23?25, 2022. The 24 full papers included in this book were carefully reviewed and selected from 74 submissions. 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