Moving Beyond Forward Simulation to Enable Data-informed Physics-based Predictions
Abstract not provided.
Publications
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Jump to search filtersGot agility? A lightweight technique for Productivity Sustainability Improvement Planning (PSIP)
Abstract not provided.
Applying Learning Techniques to Understand the Write Performance of Large-scale Parallel Filesystems
Abstract not provided.
SC19 BOF: Containers in HPC
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Benchmarking near-term quantum information processors
Abstract not provided.
The Case for Modular Generalizable Proxy Applications for Systems Software Research
Abstract not provided.
WearGP: A machine learning wear prediction framework for slurry pump impellers and casings under different operating conditions
Abstract not provided.
NNSA/CEA Collaboration: Visualization SC19 Update
Abstract not provided.
Decomposing Optimization-Based Bounds Tightening Problems Via Graph Partitioning
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SC 19 Tutorial: Best Practices
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A Case for Portability and Reproducibility of HPC Containers
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Earth System Viz: Enabling Discovery of Science at Scale
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TheKokkosC++ Performance Portability Programming Model
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Uncertainty Quantification: An Overview
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Fine-Grained Analysis of Communication Similarity between Real and Proxy Applications
Proceedings of PMBS 2019: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis
In this work we investigate the dynamic communication behavior of parent and proxy applications, and investigate whether or not the dynamic communication behavior of the proxy matches that of its respective parent application. The idea of proxy applications is that they should match their parent well, and should exercise the hardware and perform similarly, so that from them lessons can be learned about how the HPC system and the application can best be utilized. We show here that some proxy/parent pairs do not need the extra detail of dynamic behavior analysis, while others can benefit from it, and through this we also identified a parent/proxy mismatch and improved the proxy application.
SC 19 Tutorial: Getting Started with Containers on HPC
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Astra and the state of ARM in HPC
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Profiling Platform Storage Using IO500 and Mistral
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Evaluating complexity and resilience trade-offs in emerging memory inference machines
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Neural-inspired Computing at Sandia Labs - Enabling and Performing Advanced Computation
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Compatible meshfree discretization
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Modeling Assisted Atomic Precision Advanced Manufacturing (APAM) Towards Room Temperature Operation
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IMEX and ETD Methods for NonHydrostatic Atmosphere
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Advancing the Usage and Scalability of Containers in HPC
Abstract not provided.
Fast and Robust Linear Solvers based on Hierarchical Matrices (LDRD Final Report)
This report is the final report for the LDRD project "Fast and Robust Linear Solvers using Hierarchical Matrices". The project was a success. We developed two novel algorithms for solving sparse linear systems. We demonstrated their effectiveness on ill-conditioned linear systems from ice sheet simulations. We showed that in many cases, we can obtain near-linear scaling. We believe this approach has strong potential for difficult linear systems and should be considered for other Sandia and DOE applications. We also report on some related research activities in dense solvers and randomized linear algebra.
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