You're right. Would you consider integrating and contributing your sparse solver?
Joe H.  HP Software
Original Message
From: Mike Zhou [mailto:mike.zhou@interpss.org]
Sent: Wednesday, December 08, 2010 3:14 PM
To: Commons Users List
Subject: Re: [MATH] Linear equation [A] [X] = [B] solution using Sparse Matrix
Joe,
It could be 50K x 50K, however, with only less than 1% nonzero 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 <josiah.d.haswell@hp.com>wrote:
> How large? It's likely one of those pesky timecomplexity things you run
> into sometimes =(
>
> Joe H.  HP Software
>
> Original Message
> From: Mike Zhou [mailto:mike.zhou@interpss.org]
> 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 largescale 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
>
> 
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