Hi,
I need to compute 10% of smallest eigenvalues of huge (3432x3432,
12870x12870, 184756x184756) real symmetric sparse matrix (over 99,8% of
elements =0).
At first I tried to do it using GSL and in first case it take ~160s to
capure all eigenvalues. Because matrix is extremely sparse I thought
that it will be faster if I use ARPACK++ instead of gsl. I use function
ARluSymStdEig<double> dprob(ilosc_wartosci, matrix, "SM");
dprob.ChangeMaxit(10000000000);
dprob.FindEigenvectors();
where ilosc_wartosci is number of eigenvalues I want to compute.
It works, but I takes ~129s to compute 10% of all eigenvalues. I thought
I would be much faster.
My question is, if gsl is so good, ARPACK++ so bad or am I doing sth wrong.
BTW, ARPACK++ use sparse matrix in CSC format. Is it possible to write
matrix with columns consisting only zeros using this code?
Rafal
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