Hi all,
A new toolbox has been uploaded at https://atoms.scilab.org/toolboxes/scicolpack: Scicolpack is is the Scilab interface to CSCsw/ColPack (https://github.com/CSCsw/ColPack), a Graph Coloring Algorithm Package applied to efficient computation of sparse Jacobian and Hessian. When you have to compute the Jacobian of a function f or the Hessian of f knowing its gradient g, once you know its sparsity pattern, even if you have derived it symbolically, it may still be faster to estimate it by using the techniques which are used by Colpack. Roughly speaking, this works by building a graph where each vertex is associated to a column of the Jacobian or Hessian, and an edge connects to vertices/columns if they are not structurally orthogonal, i.e. have at least one non-zero term in a common row. Then a proper coloring is done on this graph: at least, two adjacent vertices cannot have the same color, but more properties of the coloring may be expected. The coloring defines a partition of the columns under the form of p subsets and the Jacobian (resp. Hessian) can be recovered from only p evaluation of directional derivatives of f (resp. g). For example, for a tridiagonal matrix the value of p is 3. In the Scilab interface these directional derivatives are approximated by using finite differences (the toolbox allows to compute them by using the complex step technique up to machine precision). This toolbox can be an nice addon to SciIpopt toolbox (https://atoms.scilab.org/toolboxes/sci_ipopt) where the Interior Point algorithm can be greatly accelerated when the Hessian of the Lagrangian is sparse. When I have time I will update the demo section of the module to add such an example. Don't hesitate to report successful uses, bugs or whishes. For the moment the toolbox is available under OSX and Linux. Any help for a Windows build is welcome ! Best, -- Stéphane Mottelet Ingénieur de recherche EA 4297 Transformations Intégrées de la Matière Renouvelable Département Génie des Procédés Industriels Sorbonne Universités - Université de Technologie de Compiègne CS 60319, 60203 Compiègne cedex Tel : +33(0)344234688 http://www.utc.fr/~mottelet _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users |
Hello,
With the help of Antoine we now have a Windows build. Moreover some glitches have been fixed (get rid of OpenMP and a failing load under macOS) and a new version 0.2 is now online on Atoms. To give it a try: --> atomsInstall scicolpack Best, S. Le 14/12/2020 à 16:50, Stéphane Mottelet a écrit : > Hi all, > > A new toolbox has been uploaded at > https://antispam.utc.fr/proxy/2/c3RlcGhhbmUubW90dGVsZXRAdXRjLmZy/atoms.scilab.org/toolboxes/scicolpack: > > Scicolpack is is the Scilab interface to CSCsw/ColPack > (https://antispam.utc.fr/proxy/2/c3RlcGhhbmUubW90dGVsZXRAdXRjLmZy/github.com/CSCsw/ColPack), > a Graph Coloring Algorithm Package applied to efficient computation of > sparse Jacobian and Hessian. > > When you have to compute the Jacobian of a function f or the Hessian > of f knowing its gradient g, once you know its sparsity pattern, even > if you have derived it symbolically, it may still be faster to > estimate it by using the techniques which are used by Colpack. Roughly > speaking, this works by building a graph where each vertex is > associated to a column of the Jacobian or Hessian, and an edge > connects to vertices/columns if they are not structurally orthogonal, > i.e. have at least one non-zero term in a common row. Then a proper > coloring is done on this graph: at least, two adjacent vertices cannot > have the same color, but more properties of the coloring may be > expected. The coloring defines a partition of the columns under the > form of p subsets and the Jacobian (resp. Hessian) can be recovered > from only p evaluation of directional derivatives of f (resp. g). For > example, for a tridiagonal matrix the value of p is 3. In the Scilab > interface these directional derivatives are approximated by using > finite differences (the toolbox allows to compute them by using the > complex step technique up to machine precision). > > This toolbox can be an nice addon to SciIpopt toolbox > (https://antispam.utc.fr/proxy/2/c3RlcGhhbmUubW90dGVsZXRAdXRjLmZy/atoms.scilab.org/toolboxes/sci_ipopt) > where the Interior Point algorithm can be greatly accelerated when the > Hessian of the Lagrangian is sparse. When I have time I will update > the demo section of the module to add such an example. > > Don't hesitate to report successful uses, bugs or whishes. For the > moment the toolbox is available under OSX and Linux. Any help for a > Windows build is welcome ! > > Best, > Stéphane Mottelet Ingénieur de recherche EA 4297 Transformations Intégrées de la Matière Renouvelable Département Génie des Procédés Industriels Sorbonne Universités - Université de Technologie de Compiègne CS 60319, 60203 Compiègne cedex Tel : +33(0)344234688 http://www.utc.fr/~mottelet _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users |
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