Indiana University-Purdue University Indianapolis (IUPUI) / LBM-IB method is useful and popular simulation technique that is adopted ubiquitously
to solve Fluid-Structure interaction problems in computational
fluid dynamics.
These problems are known for utilizing computing resources intensively while solving
mathematical equations involved in simulations. Problems involving such interactions
are omnipresent, therefore, it is eminent that a faster and accurate algorithm
exists for solving these equations, to reproduce a real-life model of such complex analytical
problems in a shorter time period. LBM-IB being inherently parallel, proves
to be an ideal candidate for developing a parallel software. This research focuses
on developing a parallel software library, LBM-IB based on the algorithm proposed
by [1] which is first of its kind that utilizes the high performance computing abilities
of supercomputers procurable today. An initial sequential version of LBM-IB is developed
that is used as a benchmark for correctness and performance evaluation of
shared memory parallel versions. Two shared memory parallel versions of LBM-IB
have been developed using OpenMP and Pthread library respectively. The OpenMP
version is able to scale well enough, as good as 83% speedup on multicore machines
for <=8 cores. Based on the profiling and instrumentation done on this version, to
improve the data-locality and increase the degree of parallelism, Pthread based data
centric version is developed which is able to outperform the OpenMP version by 53%
on manycore machines. A distributed version using the MPI interfaces on top of
the cube based Pthread version has also been designed to be used by extreme scale
distributed memory manycore systems.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/7928 |
| Date | 08 April 2015 |
| Creators | Nagar, Prateek |
| Contributors | Song, Fengguang, Zhu, Luoding, Mukhopadhyay, Snehasis |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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