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The Dartmouth implementation of the Scalable Simulation Framework (DaSSF) is a
discrete-event simulator used primarily in the simulation of networks. It
achieves high performance through parallel processing. DaSSF 1.22 requires
shared memory between all processors in order to operate. This limits the
number of processors available and the hardware platforms that can exploit
parallelism. We are interested in extending parallel DaSSF operation to
architectures without shared memory. We explore the requirements of this by
implementing parallel DaSSF using MPI as the sole form of interaction between
processors. The approaches used to achieve this can be abstracted and applied
to the current version of DaSSF. This would allow parallel simulation using
shared memory by processors within a single machine, and also at a higher
level between separate machines using distributed memory.
Undergraduate Honors Thesis. Advisor: David Nicol.
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
Or copy and paste:
James D. Chalfant, "Parallel DaSSF Discrete-Event Simulation without Shared Memory." Dartmouth Computer Science Technical Report PCS-TR99-346, June 1999.
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