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dc.contributor.advisor Mellor-Crummey, John M
dc.creatorTaffet, Philip Adam
dc.date.accessioned 2018-11-26T18:01:00Z
dc.date.available 2018-11-26T18:01:00Z
dc.date.created 2018-05
dc.date.issued 2018-04-30
dc.date.submitted May 2018
dc.identifier.citation Taffet, Philip Adam. "Understanding Congestion in High Performance Interconnection Networks Using Sampling." (2018) Master’s Thesis, Rice University. https://hdl.handle.net/1911/103413.
dc.identifier.urihttps://hdl.handle.net/1911/103413
dc.description.abstract The computational needs of many applications outstrip the capabilities of a single compute node. Communication is necessary to employ multiple nodes, but slow communication often limits application performance on multiple nodes. To improve communication performance, developers need tools that enable them to understand how their application’s communication patterns interact with the network, especially when those interactions result in congestion. Since communication performance is difficult to reason about analytically and simulation is costly, measurement-based approaches are needed. This thesis describes a new sampling-based technique to collect information about the path a packet takes and congestion it encounters. Experiments with simulations show that this strategy can distinguish problems with an application's communication patterns, its mapping onto a parallel system, and outside interference. We describe a variant of this scheme that requires only 5-6 bits of information in a monitored packet, making it practical for use in next-generation networks.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectnetwork congestion
reservoir sampling
probabilistic
high performance computing
network simulation
InfiniBand
interconnection networks
communication performance
Omni-Path
MPI
dc.title Understanding Congestion in High Performance Interconnection Networks Using Sampling
dc.type Thesis
dc.date.updated 2018-11-26T18:01:01Z
dc.type.material Text
thesis.degree.department Computer Science
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Science
dc.identifier.doihttps://doi.org/10.25611/0pec-yd57
thesis.degree.major High Performance Computing


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