| 2022 | 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 Jeffrey Nichols, Arthur Barney Maccabe, James J. Nutaro, Swaroop Pophale, Pravallika Devineni, Theresa Ahearn, Becky Verastegui |
| 2021 | A Hardware Co-design Workflow for Scientific Instruments at the Edge. Kazutomo Yoshii, Rajesh Sankaran, Sebastian Strempfer, Maksim Levental, Mike Hammer, Antonino Miceli |
| 2021 | Advanced Image Reconstruction for MCP Detector in Event Mode. Chen Zhang, Zachary Morgan |
| 2021 | An Study on the Resource Utilization and User Behavior on Titan Supercomputer. Sergio Iserte |
| 2021 | Applying Recent Machine Learning Approaches to Accelerate the Algebraic Multigrid Method for Fluid Simulations. Thorben Louw, Simon McIntosh-Smith |
| 2021 | Atomic Defect Identification with Sparse Sampling and Deep Learning. Michael C. Cao, Jonathan Schwartz, Huihuo Zheng, Yi Jiang, Robert Hovden, Yimo Han |
| 2021 | Braid-DB: Toward AI-Driven Science with Machine Learning Provenance. Justin M. Wozniak, Zhengchun Liu, Rafael Vescovi, Ryan Chard, Bogdan Nicolae, Ian T. Foster |
| 2021 | Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery. 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 |
| 2021 | Enabling ISO Standard Languages for Complex HPC Workflows. M. Graham Lopez, Jeff R. Hammond, Jack C. Wells, Tom Gibbs, Timothy B. Costa |
| 2021 | Exploring the Spatial Relationship Between Demographic Indicators and the Built Environment of a City. Ridhima Singh, Melissa R. Allen-Dumas |
| 2021 | Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks. Massimiliano Lupo Pasini, Marko Burcul, Samuel Temple Reeve, Markus Eisenbach, Simona Perotto |
| 2021 | Finding Novel Links in COVID-19 Knowledge Graph Using Graph Embedding Techniques. Ankit Patel, Saeel Shrivallabh Pai, Haresh Rengaraj Rajamohan, Manohar Bongarala, Rajanala Samyak |
| 2021 | High-Performance Ptychographic Reconstruction with Federated Facilities. Tekin Bicer, Xiaodong Yu, Daniel J. Ching, Ryan Chard, Mathew J. Cherukara, Bogdan Nicolae, Rajkumar Kettimuthu, Ian T. Foster |
| 2021 | Lessons Learned on the Interface Between Quantum and Conventional Networking. Muneer Alshowkan, Nageswara S. V. Rao, Joseph C. Chapman, Brian P. Williams, Philip G. Evans, Raphael C. Pooser, Joseph M. Lukens, Nicholas A. Peters |
| 2021 | Machine-Learning Accelerated Studies of Materials with High Performance and Edge Computing. Ying Wai Li, Peter W. Doak, Giovanni Balduzzi, Wael R. Elwasif, Eduardo F. D'Azevedo, Thomas A. Maier |
| 2021 | Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression. 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 |
| 2021 | NREL Stratus - Enabling Workflows to Fuse Data Streams, Modeling, Simulation, and Machine Learning. David Rager, Aaron Andersen |
| 2021 | NVIDIA's Cloud Native Supercomputing. Gilad Shainer, Richard L. Graham, Chris J. Newburn, Oscar R. Hernandez, Gil Bloch, Tom Gibbs, Jack C. Wells |
| 2021 | Randomized Multilevel Monte Carlo for Embarrassingly Parallel Inference. Ajay Jasra, Kody J. H. Law, Alexander Tarakanov, Fangyuan Yu |
| 2021 | Reconstructing Piezoelectric Responses over a Lattice: Adaptive Sampling of Low Dimensional Time Series Representations Based on Relative Isolation and Gradient Size. Michael R. Lindstrom, William J. Swartworth, Deanna Needell |
| 2021 | Recurrent Multi-task Graph Convolutional Networks for COVID-19 Knowledge Graph Link Prediction. Remington Kim, Yue Ning |
| 2021 | Scaling SQL to the Supercomputer for Interactive Analysis of Simulation Data. Jens Glaser, Felipe Aramburú, William Malpica, Benjamín Hernández, Matthew B. Baker, Rodrigo Aramburú |
| 2021 | Secure Collaborative Environment for Seamless Sharing of Scientific Knowledge. Srikanth B. Yoginath, Mathieu Doucet, Debsindhu Bhowmik, David Heise, Folami Alamudun, Hong-Jun Yoon, Christopher B. Stanley |
| 2021 | Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. 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 |
| 2021 | The Convergence of HPC, AI and Big Data in Rapid-Response to the COVID-19 Pandemic. 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 |
| 2021 | Towards Standard Kubernetes Scheduling Interfaces for Converged Computing. Claudia Misale, Daniel J. Milroy, Carlos Eduardo Arango Gutierrez, Maurizio Drocco, Stephen Herbein, Dong H. Ahn, Zvonko Kaiser, Yoonho Park |
| 2021 | Transitioning from File-Based HPC Workflows to Streaming Data Pipelines with openPMD and ADIOS2. 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 |
| 2021 | Understanding and Leveraging the I/O Patterns of Emerging Machine Learning Analytics. Ana Gainaru, Dmitry Ganyushin, Bing Xie, Tahsin M. Kurç, Joel H. Saltz, Sarp Oral, Norbert Podhorszki, Franz Poeschel, Axel Huebl, Scott Klasky |
| 2021 | Use It or Lose It: Cheap Compute Everywhere. Taylor L. Groves, Damian Hazen, Glenn K. Lockwood, Nicholas J. Wright |