High performance parallel adaptive simulations operating on leadership class systems are constructed from multiple pieces of software developed over many years. As increasingly complex systems are deployed new methods must be created to extract performance and scalability. This thesis addresses two key scalability limitations for unstructured mesh based simulations.
Attaining simulation performance at ever higher concurrency levels requires increased performance of transformations within each procedure, as well as the transfer of data between procedures.
Controlling the transformations requires distributing the work evenly across the processors while executing efficient data transfers requires local operations that avoid shared or contended resources. This thesis addresses these requirements through multi-criteria load balancing procedures and in-memory data transfer techniques.
Partition improvement methods defined in this work enable improved application strong scaling on over one million processors through careful control of the balancing requirements. Applied to a computational fluid dynamics simulation running on 524,288 processes with 1.2 billion elements these methods reduce the time of the dominant computational step by up to 28% versus the best existing methods.
The scalable data transfer requirement is addressed through an in-memory functional coupling that avoids the high cost of fileystem access. The methods developed are applied to two adaptive simulations in which the time required for information exchange is reduced by over an order of magnitude versus file based couplings. Three additional simulations for industrial applications are then provided that highlight an in-memory coupling and the automation of key simulation processes.
|Advisor:||Shephard, Mark S.|
|Commitee:||Bloomfield, Max O., Carrothers, Christopher D., Cutler, Barbara, Sahni, Onkar|
|School:||Rensselaer Polytechnic Institute|
|School Location:||United States -- New York|
|Source:||DAI-B 78/12(E), Dissertation Abstracts International|
|Subjects:||Engineering, Computer science|
|Keywords:||Adaptive, Mesh-Based, Scalability, Unstructured, Workflows|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be