An alternate for Householder QR linear equation solving for fixed-layout sparse matrix












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$begingroup$


This concerns sparse matrices where the sparsity pattern is known beforehand, and where the size is between 5 and up to 50, as the linear solver for a Newton Raphson non linear solver.



For smaller than 5, I use a direct inverse computation, but for problems that are bigger, I currently use a simple dense Householder pivot solver, which get slows really quickly.



I can optimize the layout of the matrix as well, but I'm not sure "usual" sparse matrix solving method could be applied here and if they could be faster than brute-force Householder QR. I feel that knowing the sparsity could be leveraged to solve the problem faster.










share|cite|improve this question











$endgroup$












  • $begingroup$
    "Householder pivot solver"? I know gaussian pivoting and Householder QR, which one is it? Why do you think "usual" sparse solvers would not work? Have you tried? Also a nice feature of iterative methods is you can reuse the preceding solution as a starting point (likely useful in a process that is supposed to be convergent).
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:07












  • $begingroup$
    @Jean-ClaudeArbaut Indeed, Householder QR (using Eigen implementation). I'm not sure because I want something faster than dense, and iterative seems contradictory. Still, if you want to implement a sparse iterative solver for something like 4-5 entries per row and columns, what would you go for?
    $endgroup$
    – Matthieu Brucher
    Dec 2 '18 at 21:14










  • $begingroup$
    Since you are using Eigen: eigen.tuxfamily.org/dox/group__TopicSparseSystems.html
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:16










  • $begingroup$
    By the way, I didn't notice the numerical-optimization tag: you may have a look at L-BFGS or sparseLM.
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:29












  • $begingroup$
    Good pointers, thanks. I usually have only a couple of iterations, but LBFGS may be worth it indeed.
    $endgroup$
    – Matthieu Brucher
    Dec 2 '18 at 21:37
















1












$begingroup$


This concerns sparse matrices where the sparsity pattern is known beforehand, and where the size is between 5 and up to 50, as the linear solver for a Newton Raphson non linear solver.



For smaller than 5, I use a direct inverse computation, but for problems that are bigger, I currently use a simple dense Householder pivot solver, which get slows really quickly.



I can optimize the layout of the matrix as well, but I'm not sure "usual" sparse matrix solving method could be applied here and if they could be faster than brute-force Householder QR. I feel that knowing the sparsity could be leveraged to solve the problem faster.










share|cite|improve this question











$endgroup$












  • $begingroup$
    "Householder pivot solver"? I know gaussian pivoting and Householder QR, which one is it? Why do you think "usual" sparse solvers would not work? Have you tried? Also a nice feature of iterative methods is you can reuse the preceding solution as a starting point (likely useful in a process that is supposed to be convergent).
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:07












  • $begingroup$
    @Jean-ClaudeArbaut Indeed, Householder QR (using Eigen implementation). I'm not sure because I want something faster than dense, and iterative seems contradictory. Still, if you want to implement a sparse iterative solver for something like 4-5 entries per row and columns, what would you go for?
    $endgroup$
    – Matthieu Brucher
    Dec 2 '18 at 21:14










  • $begingroup$
    Since you are using Eigen: eigen.tuxfamily.org/dox/group__TopicSparseSystems.html
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:16










  • $begingroup$
    By the way, I didn't notice the numerical-optimization tag: you may have a look at L-BFGS or sparseLM.
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:29












  • $begingroup$
    Good pointers, thanks. I usually have only a couple of iterations, but LBFGS may be worth it indeed.
    $endgroup$
    – Matthieu Brucher
    Dec 2 '18 at 21:37














1












1








1


1



$begingroup$


This concerns sparse matrices where the sparsity pattern is known beforehand, and where the size is between 5 and up to 50, as the linear solver for a Newton Raphson non linear solver.



For smaller than 5, I use a direct inverse computation, but for problems that are bigger, I currently use a simple dense Householder pivot solver, which get slows really quickly.



I can optimize the layout of the matrix as well, but I'm not sure "usual" sparse matrix solving method could be applied here and if they could be faster than brute-force Householder QR. I feel that knowing the sparsity could be leveraged to solve the problem faster.










share|cite|improve this question











$endgroup$




This concerns sparse matrices where the sparsity pattern is known beforehand, and where the size is between 5 and up to 50, as the linear solver for a Newton Raphson non linear solver.



For smaller than 5, I use a direct inverse computation, but for problems that are bigger, I currently use a simple dense Householder pivot solver, which get slows really quickly.



I can optimize the layout of the matrix as well, but I'm not sure "usual" sparse matrix solving method could be applied here and if they could be faster than brute-force Householder QR. I feel that knowing the sparsity could be leveraged to solve the problem faster.







linear-algebra numerical-optimization sparse-matrices






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Dec 2 '18 at 21:12







Matthieu Brucher

















asked Dec 2 '18 at 20:58









Matthieu BrucherMatthieu Brucher

1063




1063












  • $begingroup$
    "Householder pivot solver"? I know gaussian pivoting and Householder QR, which one is it? Why do you think "usual" sparse solvers would not work? Have you tried? Also a nice feature of iterative methods is you can reuse the preceding solution as a starting point (likely useful in a process that is supposed to be convergent).
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:07












  • $begingroup$
    @Jean-ClaudeArbaut Indeed, Householder QR (using Eigen implementation). I'm not sure because I want something faster than dense, and iterative seems contradictory. Still, if you want to implement a sparse iterative solver for something like 4-5 entries per row and columns, what would you go for?
    $endgroup$
    – Matthieu Brucher
    Dec 2 '18 at 21:14










  • $begingroup$
    Since you are using Eigen: eigen.tuxfamily.org/dox/group__TopicSparseSystems.html
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:16










  • $begingroup$
    By the way, I didn't notice the numerical-optimization tag: you may have a look at L-BFGS or sparseLM.
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:29












  • $begingroup$
    Good pointers, thanks. I usually have only a couple of iterations, but LBFGS may be worth it indeed.
    $endgroup$
    – Matthieu Brucher
    Dec 2 '18 at 21:37


















  • $begingroup$
    "Householder pivot solver"? I know gaussian pivoting and Householder QR, which one is it? Why do you think "usual" sparse solvers would not work? Have you tried? Also a nice feature of iterative methods is you can reuse the preceding solution as a starting point (likely useful in a process that is supposed to be convergent).
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:07












  • $begingroup$
    @Jean-ClaudeArbaut Indeed, Householder QR (using Eigen implementation). I'm not sure because I want something faster than dense, and iterative seems contradictory. Still, if you want to implement a sparse iterative solver for something like 4-5 entries per row and columns, what would you go for?
    $endgroup$
    – Matthieu Brucher
    Dec 2 '18 at 21:14










  • $begingroup$
    Since you are using Eigen: eigen.tuxfamily.org/dox/group__TopicSparseSystems.html
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:16










  • $begingroup$
    By the way, I didn't notice the numerical-optimization tag: you may have a look at L-BFGS or sparseLM.
    $endgroup$
    – Jean-Claude Arbaut
    Dec 2 '18 at 21:29












  • $begingroup$
    Good pointers, thanks. I usually have only a couple of iterations, but LBFGS may be worth it indeed.
    $endgroup$
    – Matthieu Brucher
    Dec 2 '18 at 21:37
















$begingroup$
"Householder pivot solver"? I know gaussian pivoting and Householder QR, which one is it? Why do you think "usual" sparse solvers would not work? Have you tried? Also a nice feature of iterative methods is you can reuse the preceding solution as a starting point (likely useful in a process that is supposed to be convergent).
$endgroup$
– Jean-Claude Arbaut
Dec 2 '18 at 21:07






$begingroup$
"Householder pivot solver"? I know gaussian pivoting and Householder QR, which one is it? Why do you think "usual" sparse solvers would not work? Have you tried? Also a nice feature of iterative methods is you can reuse the preceding solution as a starting point (likely useful in a process that is supposed to be convergent).
$endgroup$
– Jean-Claude Arbaut
Dec 2 '18 at 21:07














$begingroup$
@Jean-ClaudeArbaut Indeed, Householder QR (using Eigen implementation). I'm not sure because I want something faster than dense, and iterative seems contradictory. Still, if you want to implement a sparse iterative solver for something like 4-5 entries per row and columns, what would you go for?
$endgroup$
– Matthieu Brucher
Dec 2 '18 at 21:14




$begingroup$
@Jean-ClaudeArbaut Indeed, Householder QR (using Eigen implementation). I'm not sure because I want something faster than dense, and iterative seems contradictory. Still, if you want to implement a sparse iterative solver for something like 4-5 entries per row and columns, what would you go for?
$endgroup$
– Matthieu Brucher
Dec 2 '18 at 21:14












$begingroup$
Since you are using Eigen: eigen.tuxfamily.org/dox/group__TopicSparseSystems.html
$endgroup$
– Jean-Claude Arbaut
Dec 2 '18 at 21:16




$begingroup$
Since you are using Eigen: eigen.tuxfamily.org/dox/group__TopicSparseSystems.html
$endgroup$
– Jean-Claude Arbaut
Dec 2 '18 at 21:16












$begingroup$
By the way, I didn't notice the numerical-optimization tag: you may have a look at L-BFGS or sparseLM.
$endgroup$
– Jean-Claude Arbaut
Dec 2 '18 at 21:29






$begingroup$
By the way, I didn't notice the numerical-optimization tag: you may have a look at L-BFGS or sparseLM.
$endgroup$
– Jean-Claude Arbaut
Dec 2 '18 at 21:29














$begingroup$
Good pointers, thanks. I usually have only a couple of iterations, but LBFGS may be worth it indeed.
$endgroup$
– Matthieu Brucher
Dec 2 '18 at 21:37




$begingroup$
Good pointers, thanks. I usually have only a couple of iterations, but LBFGS may be worth it indeed.
$endgroup$
– Matthieu Brucher
Dec 2 '18 at 21:37










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