Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures

Abstract

The main goals were to develop new set of algorithms for scientific and geometric computing by exploiting the power and performance efficiency of heterogeneous shared memory architectures. These include multi-core CPUs and many-core GPUs. This involves design of new algorithms, development of appropriate software environments, and demonstrating their potential on a few applications. These applications include ray and path tracing for visual and sound rendering and solving the scientific models for fluid simulation. New heterogeneous algorithms will be developed to exploit CPU and GPU cores in parallel.

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Document Details

Document Type
Technical Report
Publication Date
Oct 04, 2017
Accession Number
AD1051101

Entities

People

  • Dinesh Manocha

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Propagation
  • Acoustic Waves
  • Acoustics
  • Architectural Acoustics
  • Artificial Intelligence
  • Boundary Layer
  • Collision Avoidance
  • Computational Fluid Dynamics
  • Computational Science
  • Computer Graphics
  • Differential Equations
  • Fluid Dynamics
  • Fluid Flow
  • Information Processing
  • Three Dimensional
  • Two Dimensional
  • Virtual Reality

Readers

  • Parallel and Distributed Computing.
  • Wave Propagation and Nonlinear Chaotic Dynamics.