Questions tagged [sparse-matrix]

Questions related to storage, assembly, operations, and other aspects of dealing with sparse matrices, for which only non-zero elements are stored. Questions that do not with sparse matrices directly, but other means of using sparsity should be tagged with [sparse-operator].

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Is there a permutation used in sparse QR factorizations that better locates small elements on the diagonal of R?

Is there a permutation used in sparse QR factorizations that better locates small elements on the diagonal of R to the end of the diagonal? As an example, consider the following snippet of MATLAB ...
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5 votes
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Lowest eigenvalues of a matrix with divergent entries

In high energy physics we oftentimes encounter the following problem. For a given parametrized matrix $\{H_{ij}(\Lambda)\}$, we know that in the limit $\Lambda\to\infty$ some of its entries become ...
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1 answer
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Efficiency of developing PDE solvers using sparse matrices versus loops

I am new to solving PDEs, but have been looking at different implementations of finite difference and finite volume schemes. One thing I have noticed in different implementations is that some ...
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Iterative methods for underestimate of smallest eigenvalue for large sparse matrices

I recently read the paper "EUCLIDEAN-NORM ERROR BOUNDS FOR SYMMLQ AND CG" by Estrin et al. and there they use an underestimate (i.e. something in $(0,\lambda_{min}]$) of the smallest ...
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How to find eigvals/eigvecs of huge symmetric tridiagonal matrix using multiple processes or threads?

In python, there is a function in scipy (scipy.linalg.eigh_tridiagonal) which is extremely efficient for an exact diagonalization of a symmetric tridiagonal matrix (...
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2 votes
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solve Ax=b for outrigger A matrix python

I implement Crank-Nicolson 2D finite-difference method. I get a matrix A which is banded with 1 band above and below the main diagonal, but also contains 2 additional bands , further apart from the ...
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1 answer
90 views

Sparse direct solver that works inside opened omp parellel region?

Does anyone know a library that implements sparse direct solver working in already open omp parallel region? The only library that I know that works with this requirement is Pardiso7.2 worth ~8K USD ...
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7 votes
0 answers
101 views

Can we sparse solve a few eigenvalues specified by index range?

I need to solve a few eigenvalues of a large sparse matrix specified by their index range. These indices are according to the whole eigenspectrum sorted in algebraic (not absolute value) ascending ...
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4 votes
2 answers
149 views

nnz-preserving sparse matrix multiplication

Let A and B be sparse matrices in $ \mathbb{R}^{m\times m}$ with (roughly) the same density $p$. I want to efficiently compute a matrix $C$ that in some sense is "closest" to $AB$ while ...
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2 answers
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Where can I find matrices and it's preconditioner for testing?

I want to find some kinds of matrices for testing my code such as GMRES , MINRES and so on. But I can't find some testing matrices and corresponding preconditioner to verify my program. I know some ...
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4 votes
1 answer
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Sparse least squares with a (black-box) ill-conditioned operator

It was suggested on math.stackexchange.com that I try to ask this question here. Consider a bounded linear operator $A : U \to V$ where $U$ is finite dimensional and where $V$ is a separable Hilbert ...
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A method for finding the number of eigenvectors with a given, known eigenvalue

Is there a method for finding the number of eigenvectors with a given eigenvalue? I do not need the eigenvectors themselves, and to find the eigenvectors seems quite tough, given the comments on the ...
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1 vote
1 answer
344 views

Givens rotation algorithm without matrix-matrix multiplication

I would like to implement a givenRotation algorithm without having matrix-matrix multiplication. Matrix-vector is fine or just for looping. I am to decompose a rectangular (m+1)xm Hessenberg matrix. I ...
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1 vote
1 answer
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What is the difference between Adittive Schwarz as a preprocessor and a solver?

As we all know, the Additive Schwarz approach can be used as either solver or preconditioner, however, my question is, what is the difference between the two? In other words, how to use AS as solver, ...
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1 vote
1 answer
164 views

What is the conventional approach for sparse matrix multiplication?

When you're multiplying sparse matrices against other sparse matrices or dense matrices, what is the conventional approach for each? How are the sparse matrices stored? What does matrix multiplication ...
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2 votes
1 answer
101 views

Bounds for the optimal bandwidth of 2D/3D FEM stiffness matrices

is anyone here aware of whether there exist bounds on the optimal bandwidths of 2D/3D FEM stiffness matrices? Edit: more specifically, I would like to have bounds on the minimum bandwidth after ...
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6 votes
1 answer
198 views

Algorithm for solving systems which are nearly symmetric/adjoint?

I am familiar with Cholesky decomposition and LU factorization for solving systems of linear equations. I have a problem where I have large sparse matrices (say, 1000x1000 or larger) where only one or ...
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1 answer
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Best search algorithm for optimal weight factor in SOR method

I had written an algorithm that searches for the optimal weight parameter to be implemented in the successive-over relaxation (SOR) method which worked cleanly by vectorizing the interval and for ...
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1 answer
237 views

Efficiency of scipy.sparse.linalg.expm_multiply with sparse vs unsparse vectors

From the package scipy.sparse.linalg in Python, calling expm_multiply(X, v) allows you to compute the vector ...
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3 votes
0 answers
112 views

Invert a huge sparse operator;

please help me with this question, I want to invert a huge sparse (non-circulant) this below in a $Ax=y$ equation: $$(\lambda I+ \beta D+ \sigma C)x=y$$ where I is an Identity Matrix,D is a Diagonal ...
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1 vote
0 answers
35 views

Tolerance is not satisfied in eigsh function

I am diagonalizing a sparse matrix of size $153600\times 153600$ via eigsh function. I did not set the tolerance to specific value, so it would be the default value ...
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1 vote
0 answers
54 views

Viable algorithms for efficiently solving a block matrix system with non-uniform sparsity structure

I am trying to use Newton's method to get a stationary solution for a system of equations of the following form: $$ \begin{Bmatrix} \frac{\partial x}{\partial t} \\ 0 \end{Bmatrix} = \begin{Bmatrix} f(...
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3 votes
1 answer
197 views

How can I extract the banded or block diagonal part of a sparse matrix in MATLAB?

Given a large sparse (square) matrix in MATLAB, how can I extract the banded or the block-diagonal parts (of fixed size) of it efficiently? These are useful operations when prototyping and testing ...
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3 votes
0 answers
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Solving PDEs: What is the best way to deal with non-banded/dense jacobians?

I have a system of PDEs describing atmospheric chemistry and transport. I use finite-differences to make my system of PDEs into a system of ~10,000 ODEs. I then integrate the ODEs forward in time with ...
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3 votes
1 answer
127 views

`eigsh` (Lanczos algorithm) slows down for degenerate eigenvalues

I have a complex Hermitian matrix of size about $70000\times 70000$. I want about 100 eigenvalues near 0. However, I know that every eigenvalues are two-fold degenerate. I found out that the running ...
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1 vote
1 answer
93 views

RCM better than Nested dissection? (For FEM discretizations in 2D and 3D)

I realize this might be a too general question but here goes nothing: I am trying different re-ordering strategies and checking the fill-in of $A=LU$. I have 2D ($p=1$, $h=1/40$ on $\Omega = [-1,1]^2$)...
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3 votes
0 answers
72 views

Does shift-invert method has invertibility issue?

Please note that I have nearly zero background on numerical methods. I understand the shift invert method as described in SciPy Tutorial The main argument of the above link is as follows. Suppose we ...
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2 votes
0 answers
70 views

Software for solving large systems of linear equations over gf(2)

What available solvers are there for linear equation solver over GF(2) (Boolean), capable of dealing with large sparse systems (in the 10k - 100k variables range)?
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3 answers
345 views

How to apply the boundary condition when global stiffness matrix is stored in csr format? [duplicate]

I am solving the poisson equation and I constructed the global stiffness matrix in compressed row storage format. Then I wrote the preconditioned conjugate gradient solver for solving the system of ...
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1 vote
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C.S.R method in finite element matrix assembly

I have solved the 2D Poisson equation using finite element method with simplex triangular element in MATLAB. First, I generated the triangular mesh using pdetool in ...
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1 vote
0 answers
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Nonsymmetric permutations for LU factorisation of symmetric matrix

Let $A$ be a symmetric matrix. It is then well known that computing the LU factorisation of $PAP^T$ instead of $A$ for a suitably chosen permutation matrix $P$ can greatly reduce fill-in. My question ...
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3 votes
1 answer
164 views

Nonlinear root solving libraries which accept a Jacobian in band-storage

I'm in search for a library for solving large systems of non-linear equations, similar to MINPACK, but unlike MINPACK, can accept a Jacobian in band-storage. My Jacobian is sometimes not invertible, ...
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1 vote
2 answers
138 views

Solving a specific sparse linear system without dense materialization

I need to (computationally) solve a system of equations, for the purposes of an interior point method, of the form $$ \left[\begin{array}{cc}B & A^T \\ A & 0\end{array}\right] \left[\begin{...
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12 votes
1 answer
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How to compute Singular value decomposition of a large matrix with Python

Language: Python3 Problem: I have a matrix Q of shape [51200 rows x 51200 cols] stored in a binary file, each of the element in this matrix has a data type of complex64. To load the data into memory I ...
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6 votes
1 answer
332 views

Efficiently computing $e^{tX}$ for many different values of $t$

Given an anti-Hermitian and sparse matrix $X$, I am using Python (NumPy and SciPy) to compute the matrix exponential $f(t) := e^{tX}$ for many values of $t$. The method I am currently using is to ...
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1 vote
1 answer
125 views

Complexity of solving an image differential linear system

Define an "image differential linear system" as a linear system $A\mathbf{x}=\mathbf{b}$ wherein $\mathbf{x}$ contains the ($\mathbb{R}$) pixels of an image and each row of $A$ constrains ...
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6 votes
1 answer
571 views

Parallelize Scipy iterative methods for linear equation systems(bicgstab) in Python

I need to solve linear equations system Ax = b, where A is a sparse CSR matrix with size 500 000 x 500 000. I'am using scipy.bicgstab and it takes almost 10min to solve this system on my PC and I need ...
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1 vote
0 answers
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performance comparison between PETSc and SLATE

We want to start a new project to solve a large-scale inverse problem (O(10^6) number of parameters) to invert for subsurface wave speeds. We will use FEM to solve forward and adjoint PDEs. In our ...
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0 votes
0 answers
129 views

How to make a directed graph symmetric?

Say I have a directed graph given as an adjacency matrix $A$ in CSR format represented by the arrays ia (row indexes) and ja (...
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2 votes
1 answer
38 views

In Eigen, can a sparse matrix contain vectors/objects instead of simple scalar values?

I need to have a sparse matrix whose elements are not simple numbers, but objects, e.g. a couple of floating point values and a bunch of integer indices. I am wondering if Eigen has something similar, ...
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3 votes
1 answer
162 views

Choice of iterative solver for a sparse asymmetric matrix with symmetric structure

I have a sparse $nxn$ matrix A with pretty interesting structure. It has a block structure with symmetric structure but asymmetric blocks. Expressed mathematically the block $A_{jk} = A_{kj}$ but $A_{...
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2 votes
3 answers
132 views

Create a sparse matrix

I am writing a FE program which calculates the displacements under a uniform load. I want to store the stiffness matrix in sparse form(COO) without using an external library.Assume an upper-bound for ...
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2 votes
2 answers
158 views

L1 least squares minimization with a sparse matrix

I have the following problem: $$\min_{x\in \mathbb{R}^n}\|Ax-b\|_1$$ where the matrix $A$ is large and sparse. I am looking for methods/code that can minimize this efficiently. References are very ...
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7 votes
2 answers
2k views

When is it easy to invert a sparse matrix?

(Crossposted on cstheory.SE) When is it easy to invert a sparse matrix? Specifically, I'm wondering about the cases in which matrix inversion has similar cost to sparse matrix multiplication, hence ...
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2 votes
3 answers
676 views

On the reordering of sparse matrices

I have been reading on different techniques used to reorder sparse matrices to achieve better performance, the most popular being the Cuthill-McKee or Reverse Cuthill-McKee algorithm. Most of those ...
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0 votes
0 answers
79 views

Derivative-free ill-conditioned non-linear least squares

I am looking for a package which can solve (non-linear) least squares problems without the use of derivatives (because of an expensive model), but which also deals with ill-conditioning well (such as ...
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1 vote
1 answer
318 views

Implementation of sparse matrix SVD for GPU

I have a sparse matrix $W$ which is almost-squared ($N+1 \times N$) and I would like to know the eigenvalues of $A = W^T W$. $A$ is Hermitian so the eigenvalues are real-positive valued. The usual ...
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0 votes
1 answer
280 views

Solving large sparse system

I am working on a problem with very large sparse matrices. I'd like to compute $A^{-1} B$, that is a crucial part of converting DAE to ODE (and there is no workaround). Here size of $A$ is 2E+5 x 2E+5 ...
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1 vote
1 answer
196 views

Efficient way to solve a set of linear equations $Ax=b$ when $A$ is sparse and some elements of $b$ are equal to zero

I have a set of linear equations, $Ax=b$. And about half of the elements in the right-hand side (vector $b$) are equal to zero. My system matrix $A$ is a sparse complex matrix. And $A$ is in the size ...
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7 votes
2 answers
394 views

Is there an iterative solver for dense matrices with possible zero diagonal entries?

Is there an iterative solver that can handle potentially zero entries on the central diagonal? I am implementing a polynomial fitting algorithm (up to $10^{th}$-order) and my matrix is a "...
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