I am not getting you wrong. My first (and only logical) attempt was that only.
I tried doing that and I got loads of compilation errors. Let me send them to
you in a different mail (I will need to rebuild my code again) Thanks and
Regards
Sumit
From: Karl Rupp <[email protected]>
To: Sumit Kumar <[email protected]>
Cc: "[email protected]"
<[email protected]>
Sent: Wednesday, August 5, 2015 9:56 PM
Subject: Re: [ViennaCL-devel] ViennaCL fast_copy() matrices
> I am aware of the methodology. However, is there any example / can you
> share some examples of interfacing an Eigen matrix with fast_copy ? As
> per the API, if we detect an Eigen Matrix then something specific for
> VCL & Eigen comes up.
Sumit, don't get me wrong, but this is basic C/C++. Just grab a pointer
to the internal data from an Eigen matrix with .data() and pass it to
fast_copy().
Best regards,
Karli
> ------------------------------------------------------------------------
> *From:* Karl Rupp <[email protected]>
> *To:* Sumit Kumar <[email protected]>
> *Cc:* "[email protected]"
> <[email protected]>
> *Sent:* Wednesday, August 5, 2015 7:38 PM
> *Subject:* Re: [ViennaCL-devel] ViennaCL fast_copy() matrices
>
> Hi,
>
> > I have a dense matrix (2048 x 2048) on the GPU and I want to copy it
> > back to a host matrix on the CPU (2048 x 2048). Is there any example of
> > using fast_copy() ? 2048 is a multiple of 128.
>
> examples/benchmarks/dense_blas.cpp
>
> http://viennacl.sourceforge.net/doc/namespaceviennacl.html#a92695ea6fa06cb0b9d940bb14080b62a
>
> Best regards,
> Karli
>
> > ------------------------------------------------------------------------
> > *From:* Karl Rupp <[email protected] <mailto:[email protected]>>
> > *To:* Sumit Kumar <[email protected] <mailto:[email protected]>>
> > *Cc:* "[email protected]
> <mailto:[email protected]>"
> > <[email protected]
> <mailto:[email protected]>>
> > *Sent:* Monday, August 3, 2015 1:23 AM
> > *Subject:* Re: [ViennaCL-devel] ViennaCL reductions
> >
> > Hi Sumit,
> >
> > > I was trying to run sparse matrix multiplication, but one of my
> explicit
> > > template typedefs had Int. After some digging, I found out that
> CSR only
> > > supported Float or double. Is there any reason for this? Can we also
> > > have support for other templates? (like int ?)
> >
> > It is technically possible, but we haven't implemented it yet. After 5
> > years you are the first to even ask for it ;-)
> >
> >
> > > Another thing would be the alignment order. Suppose I have a Row-major
> > > Sparse Eigen matrix, then I can copy it to a (Row-Major ?) VCL
> > > compressed matrix. What about a column-major sparse Eigen matrix?
> >
> > If you can point me to a fast, massively parallel column-major
> > matrix-vector multiplication routine, I look into it. However, as far as
> > I know, there is no such routine for general sparse matrices, hence it
> > does not make sense for us to support it.
> >
> > Best regards,
> > Karli
> >
> >
> >
> >
> >
> >
> > >
> ------------------------------------------------------------------------
> > > *From:* Karl Rupp <[email protected]
> <mailto:[email protected]> <mailto:[email protected]
> <mailto:[email protected]>>>
> > > *To:* Sumit Kumar <[email protected]
> <mailto:[email protected]> <mailto:[email protected]
> <mailto:[email protected]>>>
> > > *Cc:* "[email protected]
> <mailto:[email protected]>
> > <mailto:[email protected]
> <mailto:[email protected]>>"
> > > <[email protected]
> <mailto:[email protected]>
> > <mailto:[email protected]
> <mailto:[email protected]>>>
>
>
>
> > > *Sent:* Friday, July 31, 2015 9:04 PM
> > > *Subject:* Re: [ViennaCL-devel] ViennaCL reductions
> > >
> > > Hi Sumit,
> > >
> > > > I am aware that Eigen can do it for its matrices and I am also
> aware
> > > > that VCL cannot do it natively. My question was this:
> > > > In your example of interfacing with Eigen, you have shown a VCL
> dense
> > > > matrix interfacing with an Eigen dense matrix. Do you have any
> example
> > > > of interfacing an Eigen Sparse matrix with a VCL dense matrix?
> > >
> > > No, we don't have this.
> > >
> > >
> > >
> > >
> > > Best regards,
> > > Karli
> > >
> > >
> > >
> > >
> >
> >
> >
>
>
>
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