The Galois system provides a solution to the hard problem of parallelizing irregular algorithms using amorphous data-parallelism. The present system works on the shared-memory programming model. The programming model has limitations on the memory and processing power available to the application. A scalable distributed parallelization tool would give the application access to a very large amount of memory and processing power by interconnecting computers through a network.
This thesis presents the design for a distributed execution programming model for the Galois system. This distributed Galois system is capable of executing irregular graph based algorithms on a distributed environment. The API and programming model of the new distributed system has been designed to mirror that of the existing shared-memory Galois. This was done to enable existing applications on shared memory applications to run on distributed Galois with minimal porting effort. Finally, two existing test cases have been implemented on distributed Galois and shown to scale with increasing number of hosts and threads. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/21643 |
| Date | 22 October 2013 |
| Creators | Dhanapal, Manoj |
| Source Sets | University of Texas |
| Language | en_US |
| Detected Language | English |
| Format | application/pdf |
Page generated in 0.0025 seconds