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dc.contributor.advisorDeng, Yuefanen_US
dc.contributor.authorPowell, Reiden_US
dc.contributor.otherDepartment of Applied Mathematics and Statisticsen_US
dc.date.accessioned2012-05-15T18:05:58Z
dc.date.available2012-05-15T18:05:58Z
dc.date.issued1-Dec-10en_US
dc.date.submittedDec-10en_US
dc.identifierPowell_grad.sunysb_0771E_10407.pdfen_US
dc.identifier.urihttp://hdl.handle.net/1951/55586
dc.description.abstractAs supercomputers have reached nearly 300,000 cores with 2 petaflops in Linpack performance in June 2010, energy consumption and temperature control are posing a developmental bottleneck. We retrospectively and comparatively examine all of the available data contained in the Green500 list that launched in November 2007, and the Top500 list, and propose a novel representation and analysis of the data, highlighting major evolutionary trends.With these new insights, we introduce a new technique for generating more efficient networks by systematically interlacing bypass rings to torus networks (iBT networks). The resulting network can improve the original torus network by reducing the network diameter, node-to-node distances, and by increasing the bisection width without increasing wiring and other engineering complexity. We present and analyze the statement that a 3D iBT network proposed by our technique outperforms 4D torus networks of the same node degree. We found that interlacing rings of sizes 6 and 12 to all three dimensions of a torus network with meshes 30 30 36 generates the best network of all possible networks, including 4D torus and hypercube of approximately 32,000 nodes. This demonstrates that strategically interlacing bypass rings into a 3D torus network enhances the torus network more effectively than adding a fourth dimension, although we may generalize the claim. We also present a node-to-node distance formula for the iBT networks.en_US
dc.description.sponsorshipStony Brook University Libraries. SBU Graduate School in Department of Applied Mathematics and Statistics. Lawrence Martin (Dean of Graduate School).en_US
dc.formatElectronic Resourceen_US
dc.language.isoen_USen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.en_US
dc.subject.lcshApplied Mathematicsen_US
dc.titleAnalysis of Supercomputers and Development of a Novel Networken_US
dc.typeDissertationen_US
dc.description.advisorAdvisor(s): Yuefan Deng. Committee Member(s): Brent Lindquist; Alan Tucker; Dantong Yu.en_US
dc.mimetypeApplication/PDFen_US


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