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Ublas : |
From: Karl Meerbergen (karl.meerbergen_at_[hidden])
Date: 2007-09-07 13:11:20
Hi Feng,
I am rather worried about memory consumption. How does lu_factorize deal
with sparsity? I guess it does not reorder the rows and columns to
reduce fill in during the factorization. Without good renumbering you
may end up with a full factorization.
Hopefully, this makes clear what I want to say.
Karl
you better use a dense matrixpinacle wrote:
> Hi Karl,
>
> I understand UBLAS may be slower since it uses a lot c++ features. For
> accessing the i-th (or i+1) element in an array A, A(i) for UBLAS vector
> will be slower than A[i] for C array. But UBLAS is quite straight forward
> for me to implement general calculations comparing with using arrays with
> pointers. If the binding of UMFPACK could improve the performance to a good
> extent, I'll give it a try.
>
> BTW, I've solved my compile problem by changing the LINE 147 of lu.cpp from
> project (mci, range (i + 1, size1)) *= value_type (1) / m (i, i);
> to
> project (mci, range (i + 1, size1)) *= value_type (1);
> project (mci, range (i + 1, size1)) /= m (i, i);
>
> Hope the developer could give a fix on this file. In fact, I feel the lu.cpp
> is not well checked or maintained. I saw several discussions about it
> before, but it still remains unchanged.
>
> Cheers!
> Feng
>
> -----Original Message-----
> From: ublas-bounces_at_[hidden] [mailto:ublas-bounces_at_[hidden]]
> On Behalf Of Karl Meerbergen
> Sent: Thursday, September 06, 2007 11:33 PM
> To: ublas mailing list
> Subject: Re: [ublas] lu factorize cannot be compiled on sparse complex
> matrix?
>
> Dear Feng Gao,
>
> It surprises me that many people are trying to use ublas routines for
> solving linear systems, while excellent external software is available:
> LAPACK for dense matrices, UMFPACK, MUMPS for sparse.
>
> In your example, you are trying to solve a 5x5 system of a sparse matrix. I
> guess this is just a small test example to make sure the code works. Suppose
> you want to solve a 20,000x20,0000 sparse system. Which performance do you
> expect to obtain with lu_factorize? For a sparse matrix, this is, in
> general, going to be a disaster.
>
> I suggest to spend some time to develop a link with external software rather
> than (sorry for being so rude) wasting your time using lu_factorize. There
> are C++ bindings to UMFPACK in boost.sandbox. I am currently working on
> MUMPS bindings, which I hope to make available soon. You will have to spend
> some time installing packages and compiling and linking, maybe a day or half
> a day. It may be a frustrating and hard job, but once you have done this,
> your code will have a good performance.
>
> Have a nice day,
>
> Karl
>
>
>
> pinacle wrote:
>
>> Dear all,
>>
>> I've been using UBLAS for solving problems like Ax=b, where A is a
>> complex dense matrix, and x and b are complex dense vectors. Today, I
>> tried to change A to a sparse matrix, but I got compiling errors as:
>> Error 10 error C2784: 'matrix_binary_scalar2_traits<E1,const
>> T2,boost::numeric::ublas::scalar_divides<E1::value_type,T2>>::result_t
>> ype boost::numeric::ublas::operator /(const
>> boost::numeric::ublas::matrix_expression<E> &,const T2 &)' : could not
>> deduce template argument for 'const
>> boost::numeric::ublas::matrix_expression<E> &' from 'std::complex<double>'
>> D:\boost\boost\numeric\ublas\lu.hpp 147
>>
>> But if I use real sparse A, no error appears. So the conclusion now is
>> that lu_factorize works for real matrices no matter dense or sparse,
>> and works for complex dense matrix, but doesn't work for complex sparse
>>
> matrix.
>
>> I do need a lu_factorize (and lu_substitute of course) working for
>> complex sparse matrices. How could I solve the problem? BTW, I am
>> using boost 1.34.0.
>>
>> Here is a sample code for testing:
>>
>> #include <complex>
>> #include <iostream>
>>
>> #include <boost/numeric/ublas/storage_sparse.hpp>
>> #include <boost/numeric/ublas/matrix.hpp> #include
>> <boost/numeric/ublas/vector.hpp> #include
>> <boost/numeric/ublas/matrix_sparse.hpp>
>> #include <boost/numeric/ublas/io.hpp>
>> #include <boost/numeric/ublas/triangular.hpp>
>> #include <boost/numeric/ublas/lu.hpp>
>>
>> using namespace boost::numeric::ublas; using namespace std;
>>
>> int main(int argc, char *argv[])
>> {
>> const size_t size = 5;
>>
>> // error:
>> //compressed_matrix<complex<double> > A(size, size);
>> //compressed_matrix<complex<double> > ALU(size, size);
>> // good:
>> compressed_matrix<double> A(size, size);
>> compressed_matrix<double> ALU(size, size);
>>
>> permutation_matrix<> pm(size);
>>
>> for (size_t i=0; i<A.size1(); ++i) {
>> if (i>=1) {
>> A.push_back(i,i-1,-2.0);
>> }
>> A.push_back(i,i,4);
>> if (i+1<A.size2()) {
>> A.push_back(i,i+1,-1.0);
>> }
>> }
>> ALU = A;
>> lu_factorize(ALU,pm); // LU factorized
>>
>> cout << "A = " << A << endl;
>> cout << "ALU = " << ALU << endl;
>>
>> return EXIT_SUCCESS;
>> };
>>
>> Thanks,
>> Feng Gao
>>
>>
>> _______________________________________________
>> ublas mailing list
>> ublas_at_[hidden]
>> http://lists.boost.org/mailman/listinfo.cgi/ublas
>>
>>
>
>
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