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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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Unveiling the Interplay Between Global Link Arrangements and Network Management Algorithms on Dragonfly Networks.
Abstract not provided.
Resistive Memory Device Requirements for a Neural Algorithm Accelerator.
Abstract not provided.
Spiking Neural Algorithms for Markov Process Random Walk.
Abstract not provided.
Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening.
Abstract not provided.
Comparing Binary-Swap Algorithms for Odd Factors of Processes.
Abstract not provided.
Task-Specific Compressive Optical System Design through Genetic Algorithms.
Abstract not provided.
N-k Failure Analysis Algorithm for Identification of Extreme Events for Cascading Outage Pre-screening process
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Algorithms to Effectively Quantize Scenarios for PV Impact Analysis using QSTS Simulation.
Abstract not provided.
The Anatomy of Mr. Scan: A Dissection of Performance of an Extreme Scale GPU-Based Clustering Algorithm, In: 2014 5th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems
The emergence of leadership class systems with GPU-equipped nodes has the potential to vastly increase the performance of existing distributed applications. However, the inclusion of GPU computation into existing extreme scale distributed applications can reveal scalability issues that were absent in the CPU version. The issues exposed in scaling by a GPU can become limiting factors to overall application performance. We developed an extreme scale GPU-based application to perform data clustering on multi-billion point datasets. In this application, called Mr. Scan, we ran into several of these performance limiting issues. Through the use of complete end-to-end benchmarking of Mr. Scan (measuring time from reading and distribution to final output), we were able to identify three major sources of real world performance issues: data distribution, GPU load balancing, and system specific issues such as start-up time. These issues comprised a vast majority of the run time of Mr. Scan. Data distribution alone accounted for 68% of the total run time of Mr. Scan when processing 6.5 billion points on Cray Titan at 8192 nodes. With improvements in these areas, we have been able able to cut total run time of Mr. Scan from 17.5 minutes to 8.3 minutes when clustering 6.5 billion points.
Retinal-Inspired Algorithms for Detection of Moving Objects.
Abstract not provided.
A Parallel Graph Algorithm for Detecting Mesh Singularities in Distributed Memory Ice Sheet Simulations.
Abstract not provided.
Validation of Multi-Frame PIV Image Interrogation Algorithms in the Spectral Domain.
Abstract not provided.
Investigating the Quantum Approximate Optimization Algorithm?s Advantage over Classical Algorithms.
Abstract not provided.
AOT Data Assimilation Algorithm: Parameter Recovery, Applications, and a Nonlinear Algorithm
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