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Optimization of Elastodynamic Finite Integration Technique on Intel Xeon Phi Knights Landing ProcessorsThis work describes the development and optimization of an implementation of an isotropic elastodynamic finite integration technique (EFIT) code for parallelized computation on Intel Knights Landing (KNL) hardware. EFIT is a numerical approach resulting in standard staggered-grid finite difference equations for the elastodynamic equations of motion to simulate bulk waves is solids. The computationally efficient simulation of elastodynamic wave propagation and interactions in aerospace materials is of high-interest in the fields of nondestructive evaluation (NDE) and structural health monitoring (SHM). Ultrasonic inspection uses an ultrasonic signal, generated at the surface of the material/structure via use of a piezoelectric transducer, to propagate sound waves into the material where it interacts with any existing defects, as well as with structural boundaries and any material inhomogeneity. Reflections from defects and boundaries are then measured by a transducer. Realistic ultrasound simulation tools can significantly aid the development and optimization of inspection techniques and can assist in the interpretation of experimental data. The optimization of an elastodynamics simulation code for the KNL Many Integrated Core processor was performed. The optimization focused on data locality and vectorization. Results show that tiling of the data to exploit the cache behavior and allow for significant utilization of the KNL hardware. The MPI implementation allows for a scalable implementation enabling large problems to be simulated. The model results were validated against theoretical dispersion curves to within 2% of the group velocity, and within 0.5% of the phase velocity of the A0 mode. Aggressive use of tiling, threading, and vectorization techniques allowed for dramatically improved time to solution.
Document ID
20190026687
Acquisition Source
Langley Research Center
Document Type
Accepted Manuscript (Version with final changes)
External Source(s)
Authors
William C. Schneck
(Langley Research Center Hampton, Virginia, United States)
Elizabeth D. Gregory
(Langley Research Center Hampton, Virginia, United States)
Cara A. C. Leckey
(Langley Research Center Hampton, Virginia, United States)
Date Acquired
June 26, 2019
Publication Date
July 27, 2018
Publication Information
Publication: Journal of Computational Physics
Publisher: Elsevier
Volume: 374
Issue Publication Date: December 1, 2018
ISSN: 0021-9991
Subject Category
Structural Mechanics
Report/Patent Number
NF1676L-29501
Report Number: NF1676L-29501
ISSN: 0021-9991
Funding Number(s)
WBS: 736466.07.02.07.43.98.42
Distribution Limits
Public
Copyright
Public Use Permitted.
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