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ORCIDSMC 2021: Virtual Event
- Jeffrey Nichols
, Arthur Barney Maccabe, James J. Nutaro, Swaroop Pophale, Pravallika Devineni, Theresa Ahearn, Becky Verastegui:
Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation - 21st Smoky Mountains Computational Sciences and Engineering, SMC 2021, Virtual Event, October 18-20, 2021, Revised Selected Papers. Communications in Computer and Information Science 1512, Springer 2022, ISBN 978-3-030-96497-9
Computational Applications: Converged HPC and Artificial Intelligence
- Ajay Jasra, Kody J. H. Law, Alexander Tarakanov, Fangyuan Yu:
Randomized Multilevel Monte Carlo for Embarrassingly Parallel Inference. 3-21 - Qian Gong, Xin Liang, Ben Whitney, Jong Youl Choi, Jieyang Chen, Lipeng Wan, Stéphane Ethier, Seung-Hoe Ku, Randy Michael Churchill, Choong-Seock Chang, Mark Ainsworth, Ozan Tugluk, Todd S. Munson, David Pugmire, Richard Archibald, Scott Klasky:
Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression. 22-39 - Thorben Louw, Simon McIntosh-Smith:
Applying Recent Machine Learning Approaches to Accelerate the Algebraic Multigrid Method for Fluid Simulations. 40-57 - Suhas Somnath, Rama K. Vasudevan, Stephen Jesse, Sergei V. Kalinin, Nageswara S. V. Rao, Christopher Brumgard, Feiyi Wang, Olga A. Kuchar, Arjun Shankar, Ben Mintz, Elke Arenholz, J. Robert Michael, Sarp Oral:
Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery. 58-75
Advanced Computing Applications: Use Cases that Combine Multiple Aspects of Data and Modeling
- Massimiliano Lupo Pasini, Marko Burcul, Samuel Temple Reeve, Markus Eisenbach, Simona Perotto:
Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks. 79-98 - Franz Poeschel, Juncheng E, William F. Godoy, Norbert Podhorszki, Scott Klasky, Greg Eisenhauer, Philip E. Davis, Lipeng Wan, Ana Gainaru, Junmin Gu, Fabian Koller, René Widera, Michael Bussmann, Axel Huebl:
Transitioning from File-Based HPC Workflows to Streaming Data Pipelines with openPMD and ADIOS2. 99-118 - Ana Gainaru, Dmitry Ganyushin, Bing Xie, Tahsin M. Kurç, Joel H. Saltz, Sarp Oral, Norbert Podhorszki, Franz Poeschel, Axel Huebl, Scott Klasky:
Understanding and Leveraging the I/O Patterns of Emerging Machine Learning Analytics. 119-138 - Srikanth B. Yoginath, Mathieu Doucet, Debsindhu Bhowmik, David Heise, Folami Alamudun, Hong-Jun Yoon, Christopher B. Stanley:
Secure Collaborative Environment for Seamless Sharing of Scientific Knowledge. 139-156 - Sreenivas R. Sukumar, Jacob A. Balma, Christopher D. Rickett, Kristyn J. Maschhoff, Joseph Landman, Charles R. Yates, Amar G. Chittiboyina, Yuri K. Peterson, Aaron Vose, Kendall G. Byler, Jérôme Baudry, Ikhlas A. Khan:
The Convergence of HPC, AI and Big Data in Rapid-Response to the COVID-19 Pandemic. 157-172 - Tekin Bicer, Xiaodong Yu, Daniel J. Ching, Ryan Chard, Mathew J. Cherukara, Bogdan Nicolae, Rajkumar Kettimuthu, Ian T. Foster:
High-Performance Ptychographic Reconstruction with Federated Facilities. 173-189 - Ying Wai Li, Peter W. Doak, Giovanni Balduzzi, Wael R. Elwasif, Eduardo F. D'Azevedo, Thomas A. Maier:
Machine-Learning Accelerated Studies of Materials with High Performance and Edge Computing. 190-205
Advanced Computing Systems and Software: Connecting Instruments from Edge to Supercomputers
- Kazutomo Yoshii, Rajesh Sankaran, Sebastian Strempfer, Maksim Levental, Mike Hammer, Antonino Miceli:
A Hardware Co-design Workflow for Scientific Instruments at the Edge. 209-226 - David Rager, Aaron Andersen:
NREL Stratus - Enabling Workflows to Fuse Data Streams, Modeling, Simulation, and Machine Learning. 227-246 - Justin M. Wozniak, Zhengchun Liu, Rafael Vescovi, Ryan Chard, Bogdan Nicolae, Ian T. Foster:
Braid-DB: Toward AI-Driven Science with Machine Learning Provenance. 247-261 - Muneer Alshowkan, Nageswara S. V. Rao, Joseph C. Chapman, Brian P. Williams, Philip G. Evans, Raphael C. Pooser, Joseph M. Lukens, Nicholas A. Peters:
Lessons Learned on the Interface Between Quantum and Conventional Networking. 262-279 - Taylor L. Groves, Damian Hazen, Glenn K. Lockwood, Nicholas J. Wright:
Use It or Lose It: Cheap Compute Everywhere. 280-298
Deploying Advanced Computing Platforms: On the Road to a Converged Ecosystem
- M. Graham Lopez, Jeff R. Hammond, Jack C. Wells, Tom Gibbs, Timothy B. Costa:
Enabling ISO Standard Languages for Complex HPC Workflows. 301-309 - Claudia Misale, Daniel J. Milroy, Carlos Eduardo Arango Gutierrez, Maurizio Drocco, Stephen Herbein, Dong H. Ahn, Zvonko Kaiser, Yoonho Park:
Towards Standard Kubernetes Scheduling Interfaces for Converged Computing. 310-326 - Jens Glaser, Felipe Aramburú, William Malpica, Benjamín Hernández, Matthew B. Baker, Rodrigo Aramburú:
Scaling SQL to the Supercomputer for Interactive Analysis of Simulation Data. 327-339 - Gilad Shainer, Richard L. Graham, Chris J. Newburn, Oscar R. Hernandez, Gil Bloch, Tom Gibbs, Jack C. Wells:
NVIDIA's Cloud Native Supercomputing. 340-357
Scientific Data Challenges
- Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa:
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. 361-382 - Chen Zhang, Zachary Morgan:
Advanced Image Reconstruction for MCP Detector in Event Mode. 383-397 - Sergio Iserte:
An Study on the Resource Utilization and User Behavior on Titan Supercomputer. 398-410 - Remington Kim, Yue Ning:
Recurrent Multi-task Graph Convolutional Networks for COVID-19 Knowledge Graph Link Prediction. 411-419 - Michael R. Lindstrom, William J. Swartworth, Deanna Needell:
Reconstructing Piezoelectric Responses over a Lattice: Adaptive Sampling of Low Dimensional Time Series Representations Based on Relative Isolation and Gradient Size. 420-429 - Ankit Patel, Saeel Shrivallabh Pai, Haresh Rengaraj Rajamohan, Manohar Bongarala, Rajanala Samyak:
Finding Novel Links in COVID-19 Knowledge Graph Using Graph Embedding Techniques. 430-441 - Ridhima Singh, Melissa R. Allen-Dumas:
Exploring the Spatial Relationship Between Demographic Indicators and the Built Environment of a City. 442-454 - Michael C. Cao, Jonathan Schwartz, Huihuo Zheng, Yi Jiang, Robert Hovden, Yimo Han:
Atomic Defect Identification with Sparse Sampling and Deep Learning. 455-463
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