johnm1019
Registered Member

Hi, we currently generate our system matrix in memory (as Eigen::Matrix), then run our solver.
In the game of speed/memory tradeoff's we want to generate a version of our code that computes the system matrix on the fly. We can wrap this as a function which looks like sysMat(i,j). Ideally though, we would also wrap it as an Eigen object so that it fits easily into our existing solver and more importantly takes advantage of SSE optimizations. Is it possible to wrap an Eigen::Matrix around a function which takes the indecies you want as arguments? 
jitseniesen
Registered Member

This is perhaps best done using CwiseNullaryOp. Unfortunately, the documentation for this part of Eigen is quite lacking. You can see some examples in ticket 457 at http://eigen.tuxfamily.org/bz/show_bug.cgi?id=457 .

johnm1019
Registered Member

Thanks for that. From the comments it appears to do what I want, but the specific declaration of the header I need I cannot determine.
I want a function which looks like an Eigen::MatrixXf, and only for float's, and always 2D layout. 
jitseniesen
Registered Member

Here is an example which you can hopefully adapt to your use case. It computes the Hilbert matrix (see http://en.wikipedia.org/wiki/Hilbert_matrix):

johnm1019
Registered Member

This is awesome, thank you! Eigen is amazing.
Can you elaborate on how to set the Cost parameter, as well as in what situations supporting PacketAccess is advisable? There is no way to handoptimize my function such that calling myFunc(1,i) for i=0:3 would be any faster than calling myFunc(1,0,1,2,3)  so I assume this would be the case where PacketAccess is used? (if I could hand code a 4wide version that was faster than calling 1wide 4x?). Thanks PS  I want to give you Karma but I don't see how I can do that 
ggael
Moderator

Cost permits to control unrolling and intermediate evaluations. The cost of one product or or one addition of floats or doubles is 1. If your function is quite complex, just pust an arbitrary high number like 1000.
PacketAccess means you can provide an SIMD version. 
bcooksley
Administrator

Karma can be awarded by following the Karma link in the postbit or on the user's profile, then selecting "Rate this user".
KDE Sysadmin
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johnm1019
Registered Member

Thanks for the tip! I must say  this is outrageously difficult to find using the default theme. 
alvaros
Registered Member

Hi, I have done the above mentioned and have already wrapped my coefficient generator function with an Eigen::MatrixXf using the CwiseNullaryOp, works awesome. Now I can compute any coefficient at will by calling sysMat(i,j).
What I need to do now, is to return my CwiseNullaryOp<coeffxy, Eigen::MatrixXf>* mat as an Eigen::MatrixXf* and use this return value as an argument for the solver:
In essence, is it possible to make a Eigen::CwiseNullaryOp look exactly like an Eigen::MatrixXf ? This of course without allocating the whole matrix but rather keeping the otf capabilities of the nullaryOp? 
johnm1019
Registered Member

Or, in a similar question, can I write a function which will happily accept a true Eigen::MatrixXf* OR the CWisenullaryop<Eigen::Matrixxf>* object?

ggael
Moderator

You need to template your function. See:
http://eigen.tuxfamily.org/dox/TopicFun ... Types.html Otherwise, the coeff(i,j) method would have to be virtual, that would lead to extremely slow computations! 
alvaros
Registered Member

For the HilbertOp case above, what would be an example definition of the SIMD version of the function? Thanks in advance.

johnm1019
Registered Member

bump 
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