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Minor update to docs
Change-Id: I886f5aa1614f66b57d7fa33233afca9bb7fabb72
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@@ -8,8 +8,8 @@ Why?
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.. _chapter-features:
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* **Code Quality** - Ceres Solver has been used in production at
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Google for more than four years now. It is clean, extensively tested
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and well documented code that is actively developed and supported.
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Google since 2011. It is clean, extensively tested and well
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documented code that is actively developed and supported.
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* **Modeling API** - It is rarely the case that one starts with the
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exact and complete formulation of the problem that one is trying to
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@@ -47,10 +47,10 @@ Why?
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linear system. To this end Ceres ships with a variety of linear
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solvers - dense QR and dense Cholesky factorization (using
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`Eigen`_, `LAPACK`_ or `CUDA`_) for dense problems, sparse
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Cholesky factorization (`SuiteSparse`_, `Apple's Accelerate`_, `Eigen`_)
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for large sparse problems, custom Schur complement based dense,
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sparse, and iterative linear solvers for `bundle adjustment`_
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problems.
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Cholesky factorization (`SuiteSparse`_, `Apple's Accelerate`_,
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`Eigen`_) for large sparse problems, custom Schur complement based
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dense, sparse, and iterative linear solvers for `bundle
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adjustment`_ problems.
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- **Line Search Solvers** - When the problem size is so large that
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storing and factoring the Jacobian is not feasible or a low
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@@ -59,20 +59,21 @@ Why?
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of Non-linear Conjugate Gradients, BFGS and LBFGS.
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* **Speed** - Ceres Solver has been extensively optimized, with C++
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templating, hand written linear algebra routines and modern C++ threads
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based multithreading of the Jacobian evaluation and the linear solvers.
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templating, hand written linear algebra routines and modern C++
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threads based multithreading of the Jacobian evaluation and the
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linear solvers.
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* **GPU Acceleration** If your system supports `CUDA`_ then Ceres
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Solver can use the Nvidia GPU on your system to speed up the solver.
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* **Solution Quality** Ceres is the `best performing`_ solver on the NIST
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problem set used by Mondragon and Borchers for benchmarking
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* **Solution Quality** Ceres is the `best performing`_ solver on the
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NIST problem set used by Mondragon and Borchers for benchmarking
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non-linear least squares solvers.
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* **Covariance estimation** - Evaluate the sensitivity/uncertainty of
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the solution by evaluating all or part of the covariance
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matrix. Ceres is one of the few solvers that allows you to do
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this analysis at scale.
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matrix. Ceres is one of the few solvers that allows you to do this
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analysis at scale.
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* **Community** Since its release as an open source software, Ceres
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has developed an active developer community that contributes new
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@@ -50,6 +50,10 @@ Backward Incompatible API Changes
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Bug Fixes & Minor Changes
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-------------------------
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#. Fix handling of M_PI for MSVC (Sergiu Deitsch)
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#. Add a default value for Solver::Summary::linear_solver_ordering_type (Sameer Agarwal)
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#. Make sure that the code compiles well with CUDA 11 (Dmitriy
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Korchemkin)
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#. Rework MSVC warning suppression (Sergiu Deitsch)
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#. Add an example for EvaluationCallback (Sameer Agarwal)
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#. Add an example for IterationCallback (Sameer Agarwal)
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