Convergence depends on distribution of eigenvalues you want to compute. On the other hand, the cost also depends on the time it takes to build the preconditioner. Use -log_view to see the cost of the different steps of the computation.
Jose > El 3 jun 2022, a las 18:50, jsfaraway <[email protected]> escribió: > > hello! > > I am trying to use epsgd compute matrix's one smallest eigenvalue. And I find > a strang thing. There are two matrix A(900000*900000) and B(90000*90000). > While solve A use 371 iterations and only 30.83s, solve B use 22 iterations > and 38885s! What could be the reason for this? Or what can I do to find the > reason? > > I use" -eps_type gd -eps_ncv 300 -eps_nev 3 -eps_smallest_real ". > And there is one difference I can tell is matrix B has many small value, > whose absolute value is less than 10-6. Could this be the reason? > > Thank you! > > Runfeng Jin
