2009
DOI: 10.1109/tvcg.2008.85
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Glimmer: Multilevel MDS on the GPU

Abstract: Abstract-We present Glimmer, a new multilevel algorithm for multidimensional scaling designed to exploit modern graphics processing unit (GPU) hardware. We also present GPU-SF, a parallel, force-based subsystem used by Glimmer. Glimmer organizes input into a hierarchy of levels and recursively applies GPU-SF to combine and refine the levels. The multilevel nature of the algorithm makes local minima less likely while the GPU parallelism improves speed of computation. We propose a robust termination condition fo… Show more

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Cited by 162 publications
(102 citation statements)
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“…More recent global techniques include Part-Linear Multidimensional Projection (PLMP) [15] and Glimmer [16]. Similarly to LMDS and Pekalska's approach, PLMP initially projects a small sample of instances on the transformed space, then it employs this information to compute a linear transformation that, applied to the original space, obtains the transformed space.…”
Section: Related Workmentioning
confidence: 99%
“…More recent global techniques include Part-Linear Multidimensional Projection (PLMP) [15] and Glimmer [16]. Similarly to LMDS and Pekalska's approach, PLMP initially projects a small sample of instances on the transformed space, then it employs this information to compute a linear transformation that, applied to the original space, obtains the transformed space.…”
Section: Related Workmentioning
confidence: 99%
“…Recently, Ingram et al introduced a multilevel algorithm called Glimmer [22] which is based on force-based MDS algorithm with restriction, relaxation, and interpolation operators. Glimmer shows less sensitivity to initial configurations than GPU-SF subsystem, which is used in Glimmer [22], due to the multilevel nature.…”
Section: Background and Related Work A Avoiding Local Optima In Mdsmentioning
confidence: 99%
“…Glimmer shows less sensitivity to initial configurations than GPU-SF subsystem, which is used in Glimmer [22], due to the multilevel nature. In Glimmer's paper [22], however, SMA-COF algorithm shows better mapping quality than Glimmer. Also, the main purpose of Glimmer is to achieve speed up with less cost of quality degrade rather than mapping quality improvement.…”
Section: Background and Related Work A Avoiding Local Optima In Mdsmentioning
confidence: 99%
“…Ingram et al proposed a multi-level GPU MDS algorithm [23] based on a parallel force-based subsystem simulation. Their approach organizes datasets into a hierarchy of levels, and recursively constructs an MDS configuration.…”
Section: Gpu Accelerated Dimdsmentioning
confidence: 99%