- From: John Erickson <olyerickson@gmail.com>
- Date: Fri, 19 May 2017 05:58:47 -0400
- To: Alexander Bigerl <bigerl@informatik.uni-leipzig.de>
- Cc: Linked Data community <public-lod@w3.org>
Tensorlab? http://tensorlab.net/ On Thu, May 18, 2017 at 12:28 PM, Alexander Bigerl <bigerl@informatik.uni-leipzig.de> wrote: > Hi everyone, > > I am working on a tensor-based triple store to query triple patterns (not > full SPARQL). Therefor I'm looking for a suitable library supporting sparse > tensor product. The programming language doesn't matter. But it would be > nice if it was optimized for orthonormal-based tensors (means it doesn't > need to distinguish between co- and contravariant dimensions for > multiplication). > > In more detail: > > I represent my my data like this: > > I have tensors storing boolean values. > > They are n >= 3 dimensional and every dimension has the same size m>1000000. > > Every dimension uses a natural number index 0...m. > > The tensors are orthonormal-based so I don't need to distinguish between co- > and contraviarant dimensions. > > There are only very few true values in every tensor, so the rest of the > values is false. Therefor it should be sparse. Non-sparse is no option > because of at least 1000000^3 entries. > > I'm looking for: > > efficient sparse n-D tensor implementation with support of a fast inner > product like: Tαγβ • Dβδε = Rαγδε > > optional: support for pipelining multiple operations > > optional: support for logical and or pointwise multiplication of > equal-dimensioned tensors. > > The following libraries don't do the trick for reasons: > > Tensor flow: misses multiplication with non-dense-none-2D-matrices > scipy sparse: supports only 2D representation and would output a dense > narray for dotproduct > theano: supports only 2D sparse tensors > Shared Scientific Toolbox and Universal Java Matrix Package: don't support > multiplication of n-D sparse tensors > > Who is wandering now where the triples are: They are mapped to the > dimensions' index so that the coordinates of a true in a 3D Tensor > represents a triple. > > I would be very thankful for any comments or recommendations. > > Kind regards, > > Alexander Bigerl -- John S. Erickson, Ph.D. Director of Operations, The Rensselaer IDEA Deputy Director, Web Science Research Center (RPI) <http://idea.rpi.edu/> <olyerickson@gmail.com> Twitter & Skype: olyerickson
Received on Friday, 19 May 2017 09:59:22 UTC