I would like to ask how to properly install a comprehensive LAPACK package as e.g. is offered by the Gentoo package 'sci-libs/clapack' within a Ubuntu environment.

I am not talking about atlas here, which only offers a small part of lapack functionality, but a more general solution offering functions for e.g. eigen value problems like 'dstegr'.

Here is what I achieved so far: My favorite search command

apt-file search clapack.h

offered only two possible sources.

libatlas-dev: /usr/include/atlas/clapack.h
libfreefem++-dev: /usr/include/freefem++/clapack.h

As mentioned, the atlas version is not, what I want. The libfreefem variation on the other hand reads fine. So

apt-get install libfreefem++-dev

In addition

apt-cache search lapack

offers a lot, the most promising looking lines being

liblapack-dev - library of linear algebra routines 3 - static version
liblapack3gf - library of linear algebra routines 3 - shared version

the first package of which I installed. Now adding

#include <freefem++/clapack.h>

into my program returns an understandable long list of errors in the style

'integer', 'real', 'doublereal', ... was not declared in this scope

as in fact they were not. Anyways I am not looking for freefem or atlas but just a running, usable LAPACK implementation is there really no such thing for Ubuntu?

Rereading my own post I believe the question might also be boiled down to "Where can I obtain a comprehensive header file for 'liblapack-dev'"?

  • Did you actually install said software? Seems like the compiler is complaining about something that should'v been included but wasn't (looks like the software wasn't installed, at least not properly installed).
    – Alex
    Feb 7, 2014 at 18:05
  • Hi Alex! Yes I did. Actually I took a good look at the /usr/include/atlas/clapack.h file. It only has an include cblas.h and about 35 (give or take) function declarations. The coveted eigenvector methods are not among them. Feb 10, 2014 at 8:16
  • Or do you mean the FreeFem approach? Maybe I will follow this up today. FreeFem actually offers a load of headers some of which probably declare the missing types. But if somehow possible I would like to reduce my actually Lapack dependent source to a single include clapack.h so I will google some more before I concede to that. Feb 10, 2014 at 8:26

2 Answers 2


I got the same result by using package manager. I did the following:

sudo apt-get install libblas-dev checkinstall
sudo apt-get install libblas-doc checkinstall
sudo apt-get install liblapacke-dev checkinstall
sudo apt-get install liblapack-doc checkinstall

The libraries went in /usr/lib and the includes in /usr/include.

Thanks to Markus-Hermann for the example code in the previous post. It helped me test it out real quick. Using the default install directories I used the following command:

g++ svd_demo.cpp -I"/usr/include" -L"/usr/lib" -llapacke -lblas
  • Is this an answer? It doesn't look much like one...
    – Seth
    Dec 22, 2014 at 19:22
  • Well, what I described is a way to properly install a comprehensive LAPACK package in ubuntu. I am using ubuntu 14.04.1. I came to this page while looking to do that, so wanted to post a quicker solution than the one presented.
    – GreenEye
    Dec 22, 2014 at 20:05
  • A year later on a new computer I come back to my old post and decide to try your short solution. And what do you know... it actually works! :-) Apr 27, 2015 at 12:32
  • It works for me as well, great relief (I even skipped installing libblas-doc). Jul 31 at 17:01

Found a solution that works for me. The bottom line for those who might read this at a later time and with a similar problem: I went to the LAPACK homepage, downloaded the most recent version of LAPACK as a tar gz, unpacked it and followed the instructions issued on installation guide on the same site. Trouble I ran into: In the Makefile I had to reduce the line

all: lapack_install lib blas_testing lapack_testing


all: lapack_install lib

After that


gave me ./liblapack.a and ./libtmglib.a.

So much so Fortran. However, I want something for inserting into a C program. This means I also want LAPACKE.

It may be found in the subdirektory ./lapacke/. There is a CMakeLists.txt which I ignored, calling the already present Makefile directly (it is short and easy to read and it uses the make.inc file you create when you follow the installation guide mentioned aboce). Single drawback here was the lack of lapacke_mangling.h which I had to copy into ./lapacke/include/.

This done the call to "make" from inside the directory ./lapacke/ ran with no trouble creating ./lapacke.a and I was ready to write a little demo program:

 * svd_demo.cpp
 * Given that you put version 3.5.0 into /opt/lapack/ compile this with: 
 * g++ svd_demo.cpp -I"/opt/lapack/lapack-3.5.0/lapacke/include" \
 *   -L"/opt/lapack/lapack-3.5.0" -llapacke -llapack -lblas -lcblas
 * The order of included libraries is important!

#include <iostream>
#include <string>
#include <sstream>
#include <cstdlib>
#include <cblas.h>
#include <lapacke.h>

using namespace std;

typedef double value;

/** Column major style! */
string matrix2string(int m, int n, value* A)
  ostringstream oss;
  for (int j=0;j<m;j++)
    for (int k=0;k<n;k++)
      oss << A[j+k*m] << "\t";
    oss << endl;
  return oss.str();

int main(int argc, char** argv)
  //> Part 1. Decomposition. -----------------------------------------
  char jobu  = 'A'; // Return the complete matrix U
  char jobvt = 'A'; // Return the complete matrix VT
  int mA = 2;
  int nA = 3;
  int lda = 2;
  int ldu = 2;
  int ldvt = 3;
  int lwork = 81;
  int info = 0;
  value* A = (value*)malloc(mA*nA*sizeof(value));
  value* U = (value*)malloc(mA*mA*sizeof(value));
  value* VT = (value*)malloc(nA*nA*sizeof(value));
  value* Svec = (value*)malloc(3*sizeof(value));
  value* work = (value*)malloc(lwork*sizeof(value));

  A[0] = 1; A[2] = 2; A[4] = 4;
  A[1] = 0; A[3] = 0; A[5] = 4;

  cout << "Matrix A (will be overwritten, as is documented):" << endl <<

  // Citing lapacke.h
  //lapack_int LAPACKE_dgesvd(int matrix_order, char jobu, char jobvt,
  //   lapack_int m, lapack_int n, double* a,
  //   lapack_int lda, double* s, double* u, lapack_int ldu,
  //   double* vt, lapack_int ldvt, double* superb);

  info = LAPACKE_dgesvd(LAPACK_COL_MAJOR, jobu, jobvt, mA, nA, A, lda, Svec, U, ldu, VT, ldvt, work);
  cout << "Ran dgesvd. Let's see ..." << endl <<
    "U:" << endl << matrix2string(mA,mA,U) <<
    "Svec:" << endl << matrix2string(1,nA,Svec) <<
    "VT:" << endl << matrix2string(nA,nA,VT) <<
    "Info Code: " << info << endl << endl <<
    "All is well." << endl;
  //< ----------------------------------------------------------------
  //> Part 2. Checking the result. -----------------------------------
  value* S = (value*)malloc(mA*nA*sizeof(value));
  S[0] = Svec[0]; S[2] = 0      ; S[4] = 0      ;
  S[1] = 0      ; S[3] = Svec[1]; S[5] = 0      ;

  // Citing cblas.h
  // void cblas_dgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA,
  //   const enum CBLAS_TRANSPOSE TransB, const int M, const int N,
  //   const int K, const double alpha, const double *A,
  //   const int lda, const double *B, const int ldb,
  //   const double beta, double *C, const int ldc);

  // work := S*VT; (2x3)=(2x3)*(3x3)
  cblas_dgemm(CblasColMajor,CblasNoTrans,CblasNoTrans,mA,nA,nA,1,S,lda,VT,ldvt,0,work,lda)    ;
  cout << "Step 1: S*VT" << endl << matrix2string(2,3,work);

  // A := U*work; (2x2)*(2x3)
  cout << "A := U*S*VT:" << endl << matrix2string(mA,nA,A) << endl;
  //< ----------------------------------------------------------------
  free(A); free(U); free(VT); free(Svec); free(work); free(S);
  return EXIT_SUCCESS;

Which on my system now produces the output

1       2       4
0       0       4
Ran dgesvd. Let's see ...
-0.759729       -0.65024
-0.65024        0.759729
5.89017 1.51851 0
-0.128982       -0.257965       -0.957506
-0.42821        -0.856419       0.288414
-0.894427       0.447214        -7.48099e-18
Info Code: 0

All is well.
Step 1: S*VT
-0.759729       -1.51946        -5.63988
-0.65024        -1.30048        0.437958
A := U*S*VT:
1       2       4
-9.63558e-16    -4.86265e-17    4

In terms of BLAS I installed

libblas-dev - Basic Linear Algebra Subroutines 3, static library
libblas3gf - Basic Linear Algebra Reference implementations, shared library
libopenblas-dev - Optimized BLAS (linear algebra) library based on GotoBLAS2

Consequently in the Lapack main Makefile I used

BLASLIB = /usr/lib/openblas-base/libopenblas.a

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