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Efficient Development Review with Heat Kernel Signature in C#

Explore our project with Dafne van Kuppevelt, Vikram Doshi, and Seçkin Savaşçı for quicker development and optimal use of .NET capabilities, focusing on Laplacian matrices and Eigen decomposer. Find more at http://code.google.com/p/infomr-group-x/.

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Efficient Development Review with Heat Kernel Signature in C#

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  1. INFOMR Project Dafne van Kuppevelt ● VikramDoshi● SeçkinSavaşçı Development Review

  2. Heat Kernel Signature

  3. C# •  develop faster •  use .NET framework’s abilities •  our experience on C# and other similar languages(java) • x86 architecture • Visual Studio IDE • Google Code for project hosting •  Easy to start •  Complete package for project management •  Support git, svn & mercurial • http://code.google.com/p/infomr-group-x/ Before Development

  4. Getting Laplacian Matrices form Off Files • L = D – A •  Storage Problem Initial Parsing 45000*44999/2*1= 120 MB 450002 * 32 = 7.54 GB • ~64X Compression • Computational Overhead

  5. Storage Problem( continued) Initial Parsing • Time Problem

  6. Getting Eigen Values & Vectors from Laplacian Matrices Initial Parsing • We tried to implement our own eigen decomposer •  FAILED • We started to search for a suitable library • Our needs were: • - Structure for storing sparse symmetric matrices • - Eigen decomposer method that is specialized • for sparse symmetric matrices • partially FAILED •  We switched to trial & error for finding • a good library, our goal was now speed and good • memory usage.

  7. Experiment results with 2000 vertex model : Initial Parsing • DotNumerics • Structure for storing Symmetric matrices • Eigen Decomposer for Symmetric matrices • ~40 largest models are out of project scope due to • time and memory problems

  8. Time and Memory Problems • Largest model will take more than 250 hours to parse • For the largest model we must have ~16 GB memory space • because DotNumerics use Double precision for storing values • Overview of running on current architecture (x86): • 2GB process dedicated memory • /largeaddressaware 3 GB • We cannot make injections due to LAPACK calls • It is impossible to reach beyond 3 GB address space on x86, theoretically 4 GB • Curious Cat? Initial Parsing

  9. Prototype Initial Parsing Result : Eigen Decomposition time for 2000 vertex model? Guess?

  10. Prototype Results Initial Parsing • We didn’t change to develop on this prototype, because : • Parsing the largest one is still infeasible • Not all of us have x64 architecture

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