xLPR Best Practices Input sets running multi-processors output and post-processing.
Abstract not provided.
Sanborn, Scott Edward↗
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Results for “PROCESSOR”
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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Convolutional Back Projection on the S1 Reduced Precision Processor.
Abstract not provided.
Holzrichter, Michael W.↗
Convolutional Back Projection on the S1 Reduced Precision Processor.
Abstract not provided.
Holzrichter, Michael W.↗
HPC at Sandia: Exploring the Virtualization and Containerization of ARM64 Processors for Future HPC Workloads.
Abstract not provided.
Younge, Andrew J↗
Evaluating the Intel Skylake Xeon Processor for HPC Workloads.
Abstract not provided.
Hughes, Clayton↗
Whetstone: An accessible platform-independent method for training spiking deep neural networks for neuromorphic processors.
Abstract not provided.
Severa, William Mark↗
One Quadrillion Triangles Queried on One Million Processors
Explore the source record for details and available documents.
Computer science↗
Fault testing a synthesizable embedded processor at gate level using Virtex Ultrascale/Ultrascale+ FPGA emulation.
Abstract not provided.
Mannos, Tom↗
Evaluating the Marvell ThunderX2 Server Processor for HPC Workloads.
Abstract not provided.
Hammond, Simon David↗
Evaluating the Marvell ThunderX2 Server Processor for HPC Workloads.
Abstract not provided.
Hammond, Simon David↗
Evaluating the Marvell ThunderX2 Server Processor for HPC Workloads.
Abstract not provided.
Hammond, Simon David↗
Testing and Assessing Quantum Computing Processors at the Quantum Performance Lab.
Abstract not provided.
Blume-Kohout, Robin J↗
Benchmarking near-term quantum information processors.
Abstract not provided.
Rudinger, Kenneth Michael↗
VTK-m: A ToolKit for Scientific Visualization on Many-Core Processors More Advanced Algorithm #1 (VIS 2019 Tutorial).
Abstract not provided.
Moreland, Kenneth D.↗
VTK-m: A ToolKit for Scientific Visualization on Many-Core Processors More Advanced Algorithm #2 (VIS 2019 Tutorial).
Abstract not provided.
Moreland, Kenneth D.↗
Performance on Trinity Phase 2 (a Cray XC40 utilizing Intel Xeon Phi processors) with Acceptance Applications and Benchmarks.
Abstract not provided.
Agelastos, Anthony Michael↗
Processor and method of weighted feature importance estimation
A method includes determining a feature importance ranking for each pair of clusters of a plurality of clusters to generate a first plurality of feature importance rankings. The method further includes determining a feature importance ranking between a particular data element and each cluster to generate a second plurality of feature importance rankings. A distance value associated with each pair of clusters of the plurality of clusters is determined to generate a plurality of distance values, and a probability value associated with each data element is determined to generate a plurality of probability values. The method further includes weighting the first plurality of feature importance rankings based on the plurality of distance values to determine a first plurality of weighted feature importance rankings and weighting the second plurality of feature importance rankings based on the plurality of probability values to determine a second plurality of weighted feature importance rankings.
97 MATHEMATICS AND COMPUTING↗