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Sameer Agarwal
7a3c43b847
By virtue of the modeling layer in Ceres being block oriented, all the matrices used by Ceres are also block oriented. When doing sparse direct factorization of these matrices, the fill-reducing ordering algorithms can either be run on the block or the scalar form of these matrices. Running it on the block form exposes more of the super-nodal structure of the matrix to the Cholesky factorization routines. This leads to substantial gains in factorization performance. This changelist adds support for approximate minimium degree orderings to be computed on the block structure of the Schur complement matrix. This affects, SchurComplementSolver and VisibilityBasedPreconditioner and SparseNormalCholesky when using SuiteSparse. A bool, use_block_amd has been added to Solver::Options and bundle_adjuster.cc has been updated to allow testing with it. When combined with a multithreaded Schur elimination, speed ups can be seen quite uniformly across the board. For some problems this can be dramatic, reducing the factorization time from 70 seconds down to 17 seconds. Change-Id: I15ebb0afcbc85ada032ec8d179ee3a2f7c8d3e46