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(Extreme-Scale Parallel Mesh Generation)
(Extreme-Scale Parallel Mesh Generation)
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[[File:CDT3D.jpg|220px|CDT3D Mesh]]
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[[File:CDT3D.jpg|330px|CDT3D Mesh]]
 
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[[File:Rocket_Mesh.jpg|220px|Rocket with Engine Mesh]]
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[[File:Output_grid.jpg|220px|Output Grid Mesh]]
 
 
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|'''CDT3D Mesh''' || '''Rocket with Engine Mesh''' || '''Aircraft Mesh'''|| '''Output Grid Mesh'''
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|'''CDT3D Meshes using speculative execution model at the chip level'''|
 
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Revision as of 12:13, 8 October 2017

Extreme-Scale Parallel Mesh Generation

    CDT3D Mesh

    Rocket with Engine Mesh

    Output Grid Mesh

Overview

Finite Element Mesh Generation is a critical component for many (bio-) engineering and science applications. The goal of this project is to deliver a novel Telescopic framework for highly scalable and energy efficient codes. Domain-and application-specific knowledge and run-time system support are combined to improve accuracy of FE computations.

  • CRTC Research Sub-Group for Extreme Scale Parallel Mesh Generation, from left to right: Nikos Chrisochoides, Kevin Garner, Dana Hammond (TM from NASA/LaRC), Christos Tsolakis and Polykarpos Thomadakis.

    We have assembled a team of established leaders (see External Collaborators) that are currently developing state-of-the-art work on mesh generation and adaptivity issues relevant to NASA’s CFD 2030 Vision and will broadly impact end-user productivity of users throughout DoD and NASA.

    Objectives

    1. Design a multi-layered algorithmic and software framework for 3D tetrahedral anisotropic parallel mesh generation methods using state-of-the-art functionality supported by methods implemented in AFLR and CRTC’s telescopic approach for parallel mesh generation.
    2. Development of error-based metrics to drive an anisotropic adaptive process
    3. Design a power-aware parallel runtime software system for extreme-scale adaptive CFD computations including: (i) mesh generation & adaptation, and (ii) consistent error-based metrics for adaptation of any CFD discretization with localizable error estimates.
  • Medical Image Computing

    Computer Aided Personalized Education