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8/10/2019 Parallel Computing Cfd
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Parallel Computing in
CFD
L Sugumar
OE12S010
Department of Ocean Engineering
IIT Madras
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Contents
Introduction
Computer Memory Architectures
Parallel Programming Models
CFD
Computationally intensive task
Conclusion
References
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Introduction
Traditionally software has been written for serial
computation.
CPU executes the set of instruction one by one in
serial computation
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Parallel computing is the simultaneous use of
multiple compute resources to solve a
computational problem.
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Computer Memory Architectures Single Processor and memory(RAM)
Multiple Processor share same memory.
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Simple distributed memory architecture.
Hybrid distributed memory architecture.
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Parallel Programming Models
In software development considering thecharacteristics and capabilities of the hardware for
which the software is being build is vital.
Shared memory architecture OpenMP
Distributed memory architecture MPI
Hybrid distributed memory architecture-
(OpenMP + MPI)
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Serial code computation of 2 D steady state heat equation
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Parallel code computation of Laplace equation
in shared memory architecture.
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Parallel code computation of Laplace equation
in distributed memory architecture
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At the end of parallel computation one gets the same
temperature distribution contour as that of the serial
computation with substantial computational time reduction.
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What basically drives the CFD community to go behind
parallel computing?
Calculation of Lift and Drag of an Airfoil section in high speed
compressible flow( say transonic flow)
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Computational domain discretisationGrid generation
Big computational domain with fine grid
Far view of the grid Near view of the grid
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Can you guess many grid points are there in the above?
58500 grid points.
At Each grid points one has to solve
Mass continuity equation
XMomentum equation
Y- Momentum equation
Energy equation
Turbulence Equation, based on the turbulence model it can be
either one or two more equations.
So CFD is computationally intensive task and it needs a great
deal of memory, processing speed and storage capacity.
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High computational time and memory issue are the two
prime factors which basically drives the CFD community togo behind parallel computing.
Parallel computing is very fast, it saves time and money of
an organization.
Parallel computing is the future of the computing.
Conclusion
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References
Internet Parallel Computing Archive, wotug.ukc.ac.uk/parallel
Introduction to Parallel Computing,
www.llnl.gov/computing/tutorials/parallel_comp/#Whatis
Parallel Programming in C with MPI and OpenMP, Michael J.Quinn, McGraw Hill Higher Education, 2003
The New Turing Omnibus, A. K. Dewdney, Henry Holt and
Company, 1993
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Thank you