Joe, It could be 50K x 50K, however, with only less than 1% non-zero elements. For example, for a 2500x2500 sparse matrix, the following are my test results:
- Common math LU decomposition 54 sec - My own sparse matrix routine (Pure Java) 0.2 sec Clearly, common math lib solves the matrix as a full matrix. Thx, Mike On Wed, Dec 8, 2010 at 4:50 PM, Haswell, Joe <[email protected]>wrote: > How large? It's likely one of those pesky time-complexity things you run > into sometimes =( > > Joe H. | HP Software > > -----Original Message----- > From: Mike Zhou [mailto:[email protected]] > Sent: Wednesday, December 08, 2010 2:49 PM > To: Commons Users List > Subject: [MATH] Linear equation [A] [X] = [B] solution using Sparse Matrix > > Hi, > > I am trying to use common math library to solve large-scale liner equation > with sparse structure. Use the SpareRealMatrix interface > and OpenMapRealMatrix implementation, I defined my matrix. Then using the > LU > decomposition, > > new LUDecompositionImpl(A).getSolver().solve(B) > > I could find the solution. However, the LU based solution seems to be very > slow. I guess, it solves the sparse matrix as a full matrix. > > Question > > - Does the LUComposition implementation take full advantage of the sparse > matrix structure > - If yes, where I might be wrong? > > I am using common math lib 2.1. > > Thanks, Mike Zhou > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [email protected] > For additional commands, e-mail: [email protected] > >
