Re: [ViennaCL-devel] compressed_matrix %*% matrix_Base

[Dmitriy L. <dl...@gm...>]

Karl,

i can independently confirm the problem with prod_impl instantiation over
expression of compressed times base_matrix into matrix type.

I understand there are tests examples but something goes wrong with the
straightforward code.

We are compiling for open cl and open mp at the same time.


On Mon, Aug 8, 2016 at 11:03 AM, Andrew Palumbo <ap...@ou...> wrote:

> Hi Karli,
>
>
> I've mocked up in C++ the method that I'm trying to use from java.  Aside
> from adding some values, it looks very similar to the code that you have
> below.
>
>
> I'm getting the same compiler error hat I was getting through javacpp/JNI:
>
>
>
>     sparseDenseMmul.cpp:85:103:   required from here
>     /usr/include/viennacl/matrix.hpp:2247:36: error: no matching function
> for call to
>     ‘prod_impl(const viennacl::compressed_matrix<double>&, const
>     viennacl::matrix_base<double, long unsigned int, long int>&,
>     viennacl::matrix_base<double, long unsigned int, long int>&)’
>           viennacl::linalg::prod_impl(proxy.lhs(), proxy.rhs(), lhs);
>
>                                     ^
>     In file included from /usr/include/viennacl/matrix.hpp:28:0,
>                      from /usr/include/viennacl/linalg/
> sparse_matrix_operations.hpp:28,
>                      from /usr/include/viennacl/compressed_matrix.hpp:31,
>                      from sparseDenseMmul.cpp:7:
>     /usr/include/viennacl/linalg/matrix_operations.hpp:438:10: note:
> candidate:
>     template<class NumericT> void viennacl::linalg::prod_impl(const
>     viennacl::matrix_base<T>&, const viennacl::vector_base<T>&,
>     viennacl::vector_base<T>&)
>          void prod_impl(const matrix_base<NumericT> & mat,
>
>
> The code is below, and I've attached both the "sparseDenseMmul.cpp" file
> and the full compilation error output (very long, probably not useful)
>
>
> Thanks very much,
>
>
> Andy
>
>
>
>
>
> Attached as "sparseDenseMmul.cpp":
>
>
> #include <iostream>
> // not using openMP for this mockup
> // #define VIENNACL_WITH_OPENMP 1
> // ViennaCL includes
> #include "viennacl/forwards.h"
> #include "viennacl/compressed_matrix.hpp"
> #include "viennacl/linalg/prod.hpp"
> #include "viennacl/backend/memory.hpp"
> #include "viennacl/matrix.hpp"
> #include "viennacl/detail/matrix_def.hpp"
> #include "viennacl/tools/random.hpp"
> #include "viennacl/context.hpp"
> #include "viennacl/linalg/host_based/sparse_matrix_operations.hpp"
>
>
> // C_dense_matrix = A_compressed_matrix %*% B_dense_matrix.
>
> // compile line w/o OpenMP: g++ sparseDenseMmul.cpp
> -I/usr/include/viennacl/ -o sparseDenseMmul
>
>
>
> int main()
> {
>   // trying to recreate javacpp wrapper functionalliy as closely as
> possible
>   // so not using typedef, unsigned ints, etc, and defining templates as
> doubles
>   // creating buffers as int/double arrays and then setting pointers to
> them.
>   // (not 100% sure that this is how javacpp passes pointers but should be
> close.)
>
>
>   //typedef double       ScalarType;
>
>   // in acuallity, we cast `int`s from jni/javacpp.
>   unsigned int m = 10;
>   unsigned int n = 10;
>   unsigned long s = 5;
>
>   unsigned int NNz_A = 12;
>
>
>   // allocate buffers and set pointers (similarly to javacpp)
>   // using ints (not unsigned ints) here from jni/javacpp.
>   int A_row_jumpers[m + 1] = {0, 0, 1, 2, 4, 5, 6, 7, 9, 11, 12};
>   int *A_row_ptr = A_row_jumpers;
>
>   // using ints (not unsigned ints) here from jni/javacpp.
>   int A_col_idxs[NNz_A] = {4, 0, 2, 3, 2, 4, 0, 4, 3, 0, 3, 0};
>   int *A_col_ptr = A_col_idxs;
>
>   double A_values[NNz_A] = {0.4065367203992265, 0.04957158909682802,
> 0.3708618354358446,
>               0.5205586068847993, 0.6963900565931678, 0.8330915529787706,
> 0.32839112750638844,
>               0.4265801782090245, 0.7856168903297948, 0.14733066454561583,
> 0.9501663495824946,
>               0.9710498974366047};
>   double* A_values_ptr = A_values;
>
>
>   // using double values in Mahout setting template directlyfor our
> compressed_matrix, A
>   viennacl::compressed_matrix<double> A_compressed_matrix(m, s);
>
>   // set the ptrs for A
>   A_compressed_matrix.set(A_row_ptr, A_col_ptr, A_values_ptr, m, s,
> NNz_A);
>
>   //  B is dense s so we only need s x n values.
>   double B_values[s * n] = {0};
>
>   // add some random data to B:
>   viennacl::tools::uniform_random_numbers<double> randomNumber;
>   for (int i = 0; i< s * n; i++) {
>     B_values[i] = randomNumber();
>   }
>
>   double* B_values_ptr = B_values;
>
>
>   // for our row_major dense_matrix, B can set the double values in the
> construcor
>   // this is currently the constructor that we're using through
> scala/javacpp.
>   const viennacl::matrix<double,viennacl::row_major>
>                        B_dense_matrix(B_values_ptr, viennacl::MAIN_MEMORY,
> s, n);
>
>
>   // perform multiplication and inside of a compressed_matrix constructor
>   viennacl::matrix<double> C_dense_matrix(viennacl::
> linalg::prod(A_compressed_matrix , B_dense_matrix));
>
>
>   // print out matrix
>   std::cout << "ViennaCL: " << C_dense_matrix << std::endl;
>
>
>   // just exit with success for now if there are no runtime errors.
>
>   return EXIT_SUCCESS;
> }
>
>
> ------------------------------
> *From:* Karl Rupp <ru...@iu...>
> *Sent:* Sunday, August 7, 2016 2:20:26 PM
> *To:* Andrew Palumbo; vie...@li...
> *Subject:* Re: [ViennaCL-devel] compressed_matrix %*% matrix_Base
>
> Hi Andy,
>
> the relevant tests for sparse matrices times dense matrices are in
> tests/spmdm.cpp. In particular, I recreated a test case based on your
> description and couldn't find any issues:
>
>   viennacl::compressed_matrix<NumericT> compressed_A;
>   viennacl::matrix<NumericT, FactorLayoutT>  B1(std_A.size(), cols_rhs);
>   viennacl::matrix_base<NumericT> B1_ref(B1);
>   viennacl::matrix_base<NumericT>
> C2(viennacl::linalg::prod(compressed_A, B1_ref));
>
> compiles cleanly. Could you please provide a code snippet demonstrating
> the problem you are encountering?
>
> Thanks and best regards,
> Karli
>
>
>
> On 08/05/2016 09:04 PM, Andrew Palumbo wrote:
> > Hi Karl,
> >
> >
> > I've been trying to implement tests for:
> >
> >
> >      matrix_base<double> C = compressed_matrix<double> A %*%
> >
> >      matrix_base<double,row_major> B.
> >
> >
> > I cant find in the code or the documentation any constructor for
> > matrix_base<T>(
> >
> > matrix_expression<const viennacl::compressed_matrix<T>, const
> > viennacl::matrix_base<T>, viennacl::op_prod>)
> >
> > ie. a mixed expression of compressed_matrix and matrix_base
> >
> > and get a compilation error when I try to instantiate a:
> >
> >      matrix_base<double>(matrix_expression<const
> >      viennacl::compressed_matrix<double>, const
> > viennacl::matrix_base<double>,
> >      viennacl::op_prod>)
> >
> > Is there a transformation that I need to do from this
> >
> >      matrix_expression<compressed_matrix<double>, matrix_base<double>,
> > op_prod>
> >
> > to something else so that I may be able to initialize a matrix_base (or
> > possibly even a compressed_matrix) from it?
> >
> > The compilation error that i get is below.
> >
> > Thanks,
> >
> > Andy
> >
>
>
> ------------------------------------------------------------
> ------------------
> What NetFlow Analyzer can do for you? Monitors network bandwidth and
> traffic
> patterns at an interface-level. Reveals which users, apps, and protocols
> are
> consuming the most bandwidth. Provides multi-vendor support for NetFlow,
> J-Flow, sFlow and other flows. Make informed decisions using capacity
> planning reports. http://sdm.link/zohodev2dev
> _______________________________________________
> ViennaCL-devel mailing list
> Vie...@li...
> https://lists.sourceforge.net/lists/listinfo/viennacl-devel
>
>