# Questions tagged [lapack]

LAPACK (Linear Algebra PACKage) is a commonly used library of subroutines for numerical linear algebra tasks, including solutions of linear sets of equations, linear least squares, eigenvalue problems, and singular value decomposition. LAPACK routines may be used with fortran, C and relatives and a variety of other languages.

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### What is the relationship of BLAS, LAPACK, and other linear algebra libraries?

I have been looking into C++ linear algebra libraries for a project I've been working on. Something that I still don't have any grasp on is the connection of BLAS and LAPACK to other linear algebra ...
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### Why isn't my Matrix-Vector Multiplication Scaling?

Sorry for the long post but I wanted to include everything that I thought was relevant in the first go. What I want I am implementing a parallel version of Krylov Subspace Methods for Dense Matrices. ...
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### Understanding how Numpy does SVD

I have been using different methods to calculate both the rank of a matrix and the solution of a matrix system of equations. I came across the function linalg.svd. Comparing this to my own effort of ...
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### Is there any benefit to compiling LAPACK from source versus installing the prebuilt package from Ubuntu?

I know that ATLAS is able to optimize itself for the machine it is compiled on and thus maximum benefits are found by compiling from source. Is there any benefit to compiling LAPACK from source? It ...
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### Rapidly determining whether or not a dense matrix is of low rank

In a software project that I'm working on, certain computations are vastly easier for dense low-rank matrices. Some problem instances involve dense low-rank matrices, but they're given to me in full, ...
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### solve $xA=b$ for $x$ using LAPACK and BLAS

I am porting an existing code from MATLAB to C++ and have a linear system to solve $xA=b$ (rather than the more typical form $Ax=b$) The matrix $A$ is dense, and of general form, but is no larger ...
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### What are the fastest available implementations of BLAS/LAPACK or other linear algebra routines on GPU systems?

nVidia, for example, has CUBLAS, which promises 7-14x speedup. Naively, this is nowhere near the theoretical throughput of any of nVidia's GPU cards. What are the challenges in speeding up linear ...
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### What is the corresponding LAPACK function behind Matlab [Q,R,E]=qr(A)?

I currently trying to cheaply compute a good rank estimate for a matrix $A$. Therefore I compute a columnt pivoting QR decompostion using [Q,R,E]=qr(A) in ...
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### Optimized open source BLAS / LAPACK package

I was wondering what is a more optimized open source BLAS/LAPACK package with respect to modern multi-core processors (Haswell and beyond). Is there any distribution that can attain performance close ...
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### How to start using LAPACK in c++?

I'm new to computational science and I already have learned basic methods for integration, interpolation, methods like RK4, Numerov etc on c++ but recently my professor asked me to learn how to use ...
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### Matrix exponential of a skew-Hermitian matrix with fortran 95 and LAPACK

I'm just getting tucked into fortran 95 for some quantum mechanics simulations. Honestly, I've been spoiled by Octave so I've taken matrix exponentiation for granted. Given a (small, $n\leq 36$) skew-...
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### What is the reason that LAPACK uses $\tau$ in QR decomposition (instead of normalizing the reflection vector)?

LAPACK's QR routine stores Q as Householder reflectors. It scales the reflection vector $v$ with $1/v_1$, so the first element of the result becomes $1$, so it doesn't have to be stored. And it stores ...
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### Benchmark problems for eigenvalue reordering algorithms sought

Every real matrix $A$ can be reduce to real Schur form $T = U^T A U$ using an orthogonal similiary transform $U$. Here the matrix $T$ is quasi-triangular form with 1 by 1 or 2 by 2 blocks on the main ...
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### Matrix exponential of a real asymmetric matrix with Fortran 95 and LAPACK

I recently asked a question along the same lines for skew-Hermitian matrices. Inspired by the success of that question, and after banging my head against a wall for a couple of hours, I'm looking at ...
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### Does PETSc ever make use of LAPACK libraries for sparse matrix math?

Does compiling PETSc with an external BLAS/LAPACK library significantly affect performance on sparse matrices, or does it only use those libraries for dense matrix math?
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### Solving a sparse and highly ill-conditioned system

I intend to solve Ax = b where A is complex, sparse, unsymmetric and highly ill-conditioned (condition number ~ 1E+20) square or rectangular matrix. I have been able to solve the system with ZGELSS in ...
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### Matrix Balancing Algorithm

I have been writing a control system toolbox from scratch and purely in Python3 (shameless plug : harold ). From my past research, I have always complaints about ...
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### How does LAPACK solve tridiagonal systems and why?

In my project I have to solve a couple of tridiagonal matrices at every time step, so it is crucial to have a good solver for those. I did my own implementation, just the classical way to do it ...
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### Fast vector - “diagonal” matrix multiplication

Let $\mathbf{1}\in\mathbb{R}^d$ be a vector with all elements equal to $1$. Define: \mathbf{D} = \mathrm{diag}(\mathbf{1}^\top,\mathbf{1}^\top,\ldots,\mathbf{1}^\top) = \begin{bmatrix} 1 \cdots 1 &...
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### Fast c++ library to solve very big sparse systems

I am working on a project with electrical circuits, where I am trying to compute the voltages at all the nodes of an electrical circuit. I know that the electrical circuit is a perfect grid, so each ...
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### BLAS, LAPACK or ATLAS for Matrix Multiplication in C

I am trying to find the most optimized way to perform Matrix Multiplication of very large sizes in C language and under Windows 7 or Ubuntu 14.04. And searching led me to BLAS, LAPACK and ATLAS. ...
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### How many operations are needed for LAPACK's zgesv to solve a linear system?

I have a linear system of complex numbers. I am using LAPACK' zgesv (actually I am using intel MKL LAPACKE, but I am assuming the algorithm is the same). No assumption can be made about the system. I ...
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### Impact of frequent row major / column major conversions using LAPACK/BLAS?

If you call a library like LAPACK or BLAS (which are written in FORTRAN and use column major order) from a C-like language that uses row major order, won't you lose performance and use a lot of memory ...
### Optimized parallel routine for $X' W X$ with $W$ diagonal
$X$ is a dense matrix of real doubles, typically of size 20 million rows and 500 columns, and $W$ is a diagonal matrix of real, non-negative doubles stored as a vector. I'm working in C and have ...