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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Projecting Performance Data Over Simulation Geometry Using SOSflow and ALPINE
Abstract not provided
Human performance differences between drawing-based and model-based reference materials.
Abstract not provided.
Information Design for XR Immersive Environments: Challenges and Opportunities.
Abstract not provided.
Scaling Productivity and Innovation on the Path to Exascale with a ?Team of Teams? Approach.
Abstract not provided.
Effects of Note-Taking Method on Knowledge Transfer in Inspection Tasks.
Abstract not provided.
The Impact of Information Presentation on Visual Inspection Performance in the International Nuclear Safeguards Domain.
Abstract not provided.
Enabling Resilience in Asynchronous Many-Task Programming Models.
Abstract not provided.
Evaluating the Influence of Size Effects on Load-Displacement Behavior and Failure in Threaded Fasteners Part I: Experimental Testing.
Abstract not provided.
Solid Cylindrical Bar Torsion for Characterizing Shear Plastic Deformation and Failure.
Abstract not provided.
Hydrodynamic Richtmyer-Meshkov Instability of Metallic Solids Used to Assess Material Deformation at High Strain-Rates
Abstract not provided
Mesh-hardened finite element analysis through a Generalized Moving Least-Squares approximation of variational problems.
Abstract not provided.
$\mathrm{RADICAL}$-Pilot and $\mathrm{PMIx}$/$\mathrm{PRRTE}$: Executing Heterogeneous Workloads at Large Scale on Partitioned $\mathrm{HPC}$ Resources
Execution of heterogeneous workflows on high-performance computing (HPC) platforms present unprecedented resource management and execution coordination challenges for runtime systems. Task heterogeneity increases the complexity of resource and execution management, limiting the scalability and efficiency of workflow execution. Re-source partitioning and distribution of tasks execution over portioned re-sources promises to address those problems but we lack an experimental evaluation of its performance at scale. Here this paper provides a performance evaluation of the Process Management Interface for Exascale (PMIx) and its reference implementation PRRTE on the leadership-class HPC plat-form Summit, when integrated into a pilot-based runtime system called RADICAL-Pilot. We partition resources across multiple PRRTE Distributed Virtual Machine (DVM) environments, responsible for launching tasks via the PMIx interface. We experimentally measure the work-load execution performance in terms of task scheduling/launching rate and distribution of DVM task placement times, DVM startup and termination overheads on the Summit leadership-class HPC platform. Integrated solution with PMIx/PRRTE enables using an abstracted, standardized set of interfaces for orchestrating the launch process, dynamic process management and monitoring capabilities. It extends scaling capabilities allowing to overcome a limitation of other launching mechanisms (e.g., JSM/LSF). Explored different DVM setup configurations provide insights on DVM performance and a layout to leverage it. Our experimental results show that heterogeneous workload of 65,500 tasks on 2048 nodes, and partitioned across 32 DVMs, runs steady with resource utilization not lower than 52%. While having less concurrently executed tasks resource utilization is able to reach up to 85%, based on results of heterogeneous workload of 8200 tasks on 256 nodes and 2 DVMs.
Validation of Grid-Based Hex Meshes With Computational Solid Mechanics.
Abstract not provided.
Parameterized Reduced Order Models Constructed Using Hyper Dual Numbers.
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Overview of the Dynamic Characterization at the DOE/SNL SWiFT Wind Facility.
Abstract not provided.
GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics1
Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally. However, there are limitations to this approach which cause vertex centric algorithms to under-perform due to poor compute to communication overhead ratio and slow convergence of iterative superstep. In this paper we introduce GoFFish a scalable sub-graph centric framework co-designed with a distributed persistent graph storage for large scale graph analytics on commodity clusters. We introduce a sub-graph centric programming abstraction that combines the scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation.